Goal templates — Data Mesh Roles — P2

Data Mesh Roles · Data Mesh Roles · P2 — Developing Professional

These are canon-derived frames, not advice: every line is either verbatim JobFrame canon text or a fixed template wrapping it. ⟨target⟩ / ⟨baseline⟩ / ⟨date⟩ are placeholders for the manager to fill in. Nothing here is generated by AI — rows are omitted, never invented, when the canon lacks the underlying field.

SMART goals

One row per canon core output / responsibility this level owns.

JFM responsibility (P2)

Writes SQL and dbt transformations that convert raw domain data into final data products compliant with agreed-upon data contracts and governance standards.

Specific: Deliver: "Writes SQL and dbt transformations that convert raw domain data into final data products compliant with agreed-upon data contracts and governance standards."
Measurable: Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
Achievable: Scoped to this level's jfm complexity/problem-solving rubric: "Solves conventional transformation and modeling problems in familiar contexts; exercises judgment within defined procedures and escalates contract or interoperability questions."
Relevant: Advances the Data Mesh Roles · Data Mesh Roles mandate for a P2 — Developing Professional.
Time-bound: ⟨date⟩

JFM responsibility (P2)

Builds, maintains, and evolves domain-specific data modeled as a product within a single domain, consuming established standards rather than authoring them.

Specific: Deliver: "Builds, maintains, and evolves domain-specific data modeled as a product within a single domain, consuming established standards rather than authoring them."
Measurable: Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
Achievable: Scoped to this level's jfm complexity/problem-solving rubric: "Solves conventional transformation and modeling problems in familiar contexts; exercises judgment within defined procedures and escalates contract or interoperability questions."
Relevant: Advances the Data Mesh Roles · Data Mesh Roles mandate for a P2 — Developing Professional.
Time-bound: ⟨date⟩

JFM responsibility (P2)

Works closely with a Data Product Owner to understand user expectations and translate them into pipeline changes on Snowflake, BigQuery, or Databricks.

Specific: Deliver: "Works closely with a Data Product Owner to understand user expectations and translate them into pipeline changes on Snowflake, BigQuery, or Databricks."
Measurable: Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
Achievable: Scoped to this level's jfm complexity/problem-solving rubric: "Solves conventional transformation and modeling problems in familiar contexts; exercises judgment within defined procedures and escalates contract or interoperability questions."
Relevant: Advances the Data Mesh Roles · Data Mesh Roles mandate for a P2 — Developing Professional.
Time-bound: ⟨date⟩

JFM responsibility (P2)

Ensures interoperability with other data products on the mesh by exchanging data through existing well-defined contracts in Parquet, Avro, or Iceberg.

Specific: Deliver: "Ensures interoperability with other data products on the mesh by exchanging data through existing well-defined contracts in Parquet, Avro, or Iceberg."
Measurable: Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
Achievable: Scoped to this level's jfm complexity/problem-solving rubric: "Solves conventional transformation and modeling problems in familiar contexts; exercises judgment within defined procedures and escalates contract or interoperability questions."
Relevant: Advances the Data Mesh Roles · Data Mesh Roles mandate for a P2 — Developing Professional.
Time-bound: ⟨date⟩

JFM responsibility (P2)

Develops working mastery of SQL, Python, and one cloud platform (AWS, GCP, or Azure) through hands-on delivery under defined procedures.

Specific: Deliver: "Develops working mastery of SQL, Python, and one cloud platform (AWS, GCP, or Azure) through hands-on delivery under defined procedures."
Measurable: Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
Achievable: Scoped to this level's jfm complexity/problem-solving rubric: "Solves conventional transformation and modeling problems in familiar contexts; exercises judgment within defined procedures and escalates contract or interoperability questions."
Relevant: Advances the Data Mesh Roles · Data Mesh Roles mandate for a P2 — Developing Professional.
Time-bound: ⟨date⟩

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1. Writes SQL and dbt transformations that convert raw domain data into final data products compliant with agreed-upon data contracts and governance standards.  [source: JFM responsibility (P2)]
   Specific:    Deliver: "Writes SQL and dbt transformations that convert raw domain data into final data products compliant with agreed-upon data contracts and governance standards."
   Measurable:  Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
   Achievable:  Scoped to this level's jfm complexity/problem-solving rubric: "Solves conventional transformation and modeling problems in familiar contexts; exercises judgment within defined procedures and escalates contract or interoperability questions."
   Relevant:    Advances the Data Mesh Roles · Data Mesh Roles mandate for a P2 — Developing Professional.
   Time-bound:  ⟨date⟩

2. Builds, maintains, and evolves domain-specific data modeled as a product within a single domain, consuming established standards rather than authoring them.  [source: JFM responsibility (P2)]
   Specific:    Deliver: "Builds, maintains, and evolves domain-specific data modeled as a product within a single domain, consuming established standards rather than authoring them."
   Measurable:  Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
   Achievable:  Scoped to this level's jfm complexity/problem-solving rubric: "Solves conventional transformation and modeling problems in familiar contexts; exercises judgment within defined procedures and escalates contract or interoperability questions."
   Relevant:    Advances the Data Mesh Roles · Data Mesh Roles mandate for a P2 — Developing Professional.
   Time-bound:  ⟨date⟩

3. Works closely with a Data Product Owner to understand user expectations and translate them into pipeline changes on Snowflake, BigQuery, or Databricks.  [source: JFM responsibility (P2)]
   Specific:    Deliver: "Works closely with a Data Product Owner to understand user expectations and translate them into pipeline changes on Snowflake, BigQuery, or Databricks."
   Measurable:  Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
   Achievable:  Scoped to this level's jfm complexity/problem-solving rubric: "Solves conventional transformation and modeling problems in familiar contexts; exercises judgment within defined procedures and escalates contract or interoperability questions."
   Relevant:    Advances the Data Mesh Roles · Data Mesh Roles mandate for a P2 — Developing Professional.
   Time-bound:  ⟨date⟩

4. Ensures interoperability with other data products on the mesh by exchanging data through existing well-defined contracts in Parquet, Avro, or Iceberg.  [source: JFM responsibility (P2)]
   Specific:    Deliver: "Ensures interoperability with other data products on the mesh by exchanging data through existing well-defined contracts in Parquet, Avro, or Iceberg."
   Measurable:  Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
   Achievable:  Scoped to this level's jfm complexity/problem-solving rubric: "Solves conventional transformation and modeling problems in familiar contexts; exercises judgment within defined procedures and escalates contract or interoperability questions."
   Relevant:    Advances the Data Mesh Roles · Data Mesh Roles mandate for a P2 — Developing Professional.
   Time-bound:  ⟨date⟩

5. Develops working mastery of SQL, Python, and one cloud platform (AWS, GCP, or Azure) through hands-on delivery under defined procedures.  [source: JFM responsibility (P2)]
   Specific:    Deliver: "Develops working mastery of SQL, Python, and one cloud platform (AWS, GCP, or Azure) through hands-on delivery under defined procedures."
   Measurable:  Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
   Achievable:  Scoped to this level's jfm complexity/problem-solving rubric: "Solves conventional transformation and modeling problems in familiar contexts; exercises judgment within defined procedures and escalates contract or interoperability questions."
   Relevant:    Advances the Data Mesh Roles · Data Mesh Roles mandate for a P2 — Developing Professional.
   Time-bound:  ⟨date⟩

OKRs

Objectives from this level's core outputs; key results only where a real dimension or capability backs them.

JFM responsibility (P2)

Writes SQL and dbt transformations that convert raw domain data into final data products compliant with agreed-upon data contracts and governance standards.

From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Writes SQL and dbt transformations that convert raw domain data into final data products compliant with agreed-upon data contracts and governance standards."
Evidence at this level's scope bar: "Defined deliverables / small features" — ⟨target⟩ by ⟨date⟩

JFM responsibility (P2)

Builds, maintains, and evolves domain-specific data modeled as a product within a single domain, consuming established standards rather than authoring them.

From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Builds, maintains, and evolves domain-specific data modeled as a product within a single domain, consuming established standards rather than authoring them."
Evidence at this level's autonomy bar: "General supervision; reviewed at milestones" — ⟨target⟩ by ⟨date⟩

JFM responsibility (P2)

Works closely with a Data Product Owner to understand user expectations and translate them into pipeline changes on Snowflake, BigQuery, or Databricks.

From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Works closely with a Data Product Owner to understand user expectations and translate them into pipeline changes on Snowflake, BigQuery, or Databricks."
Evidence at this level's complexity bar: "Some non-routine problems; applies established patterns" — ⟨target⟩ by ⟨date⟩

JFM responsibility (P2)

Ensures interoperability with other data products on the mesh by exchanging data through existing well-defined contracts in Parquet, Avro, or Iceberg.

From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Ensures interoperability with other data products on the mesh by exchanging data through existing well-defined contracts in Parquet, Avro, or Iceberg."
Evidence at this level's impact bar: "Own and immediate-team deliverables" — ⟨target⟩ by ⟨date⟩

JFM responsibility (P2)

Develops working mastery of SQL, Python, and one cloud platform (AWS, GCP, or Azure) through hands-on delivery under defined procedures.

From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Develops working mastery of SQL, Python, and one cloud platform (AWS, GCP, or Azure) through hands-on delivery under defined procedures."
Evidence at this level's decision rights bar: "Routine technical choices within guidance" — ⟨target⟩ by ⟨date⟩

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Objective 1: Writes SQL and dbt transformations that convert raw domain data into final data products compliant with agreed-upon data contracts and governance standards. [source: JFM responsibility (P2)]
KR1. From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Writes SQL and dbt transformations that convert raw domain data into final data products compliant with agreed-upon data contracts and governance standards."
KR2. Evidence at this level's scope bar: "Defined deliverables / small features" — ⟨target⟩ by ⟨date⟩

Objective 2: Builds, maintains, and evolves domain-specific data modeled as a product within a single domain, consuming established standards rather than authoring them. [source: JFM responsibility (P2)]
KR1. From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Builds, maintains, and evolves domain-specific data modeled as a product within a single domain, consuming established standards rather than authoring them."
KR2. Evidence at this level's autonomy bar: "General supervision; reviewed at milestones" — ⟨target⟩ by ⟨date⟩

Objective 3: Works closely with a Data Product Owner to understand user expectations and translate them into pipeline changes on Snowflake, BigQuery, or Databricks. [source: JFM responsibility (P2)]
KR1. From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Works closely with a Data Product Owner to understand user expectations and translate them into pipeline changes on Snowflake, BigQuery, or Databricks."
KR2. Evidence at this level's complexity bar: "Some non-routine problems; applies established patterns" — ⟨target⟩ by ⟨date⟩

Objective 4: Ensures interoperability with other data products on the mesh by exchanging data through existing well-defined contracts in Parquet, Avro, or Iceberg. [source: JFM responsibility (P2)]
KR1. From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Ensures interoperability with other data products on the mesh by exchanging data through existing well-defined contracts in Parquet, Avro, or Iceberg."
KR2. Evidence at this level's impact bar: "Own and immediate-team deliverables" — ⟨target⟩ by ⟨date⟩

Objective 5: Develops working mastery of SQL, Python, and one cloud platform (AWS, GCP, or Azure) through hands-on delivery under defined procedures. [source: JFM responsibility (P2)]
KR1. From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Develops working mastery of SQL, Python, and one cloud platform (AWS, GCP, or Azure) through hands-on delivery under defined procedures."
KR2. Evidence at this level's decision rights bar: "Routine technical choices within guidance" — ⟨target⟩ by ⟨date⟩

MBO areas

Key result areas from this level's responsibilities, each with a standard grounded in the canon leveling rubric where one exists.

Area	Standard	Target	Due
Writes SQL and dbt transformations that convert raw domain data into final data products compliant with agreed-upon data contracts and governance standards.	Consistent with this level's jfm knowledge-application rubric: "Applies SQL, Python/dbt, and one cloud platform to build transformations within a single domain, consuming established data contracts and governance standards rather than defining them."	⟨target⟩	⟨date⟩
Builds, maintains, and evolves domain-specific data modeled as a product within a single domain, consuming established standards rather than authoring them.	Consistent with this level's jfm knowledge-application rubric: "Applies SQL, Python/dbt, and one cloud platform to build transformations within a single domain, consuming established data contracts and governance standards rather than defining them."	⟨target⟩	⟨date⟩
Works closely with a Data Product Owner to understand user expectations and translate them into pipeline changes on Snowflake, BigQuery, or Databricks.	Consistent with this level's jfm knowledge-application rubric: "Applies SQL, Python/dbt, and one cloud platform to build transformations within a single domain, consuming established data contracts and governance standards rather than defining them."	⟨target⟩	⟨date⟩
Ensures interoperability with other data products on the mesh by exchanging data through existing well-defined contracts in Parquet, Avro, or Iceberg.	Consistent with this level's jfm knowledge-application rubric: "Applies SQL, Python/dbt, and one cloud platform to build transformations within a single domain, consuming established data contracts and governance standards rather than defining them."	⟨target⟩	⟨date⟩
Develops working mastery of SQL, Python, and one cloud platform (AWS, GCP, or Azure) through hands-on delivery under defined procedures.	Consistent with this level's jfm knowledge-application rubric: "Applies SQL, Python/dbt, and one cloud platform to build transformations within a single domain, consuming established data contracts and governance standards rather than defining them."	⟨target⟩	⟨date⟩

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1. Area: Writes SQL and dbt transformations that convert raw domain data into final data products compliant with agreed-upon data contracts and governance standards.  [source: JFM responsibility (P2) — reused, no distinct responsibility content]
   Standard: Consistent with this level's jfm knowledge-application rubric: "Applies SQL, Python/dbt, and one cloud platform to build transformations within a single domain, consuming established data contracts and governance standards rather than defining them."
   Target:   ⟨target⟩   Due: ⟨date⟩

2. Area: Builds, maintains, and evolves domain-specific data modeled as a product within a single domain, consuming established standards rather than authoring them.  [source: JFM responsibility (P2) — reused, no distinct responsibility content]
   Standard: Consistent with this level's jfm knowledge-application rubric: "Applies SQL, Python/dbt, and one cloud platform to build transformations within a single domain, consuming established data contracts and governance standards rather than defining them."
   Target:   ⟨target⟩   Due: ⟨date⟩

3. Area: Works closely with a Data Product Owner to understand user expectations and translate them into pipeline changes on Snowflake, BigQuery, or Databricks.  [source: JFM responsibility (P2) — reused, no distinct responsibility content]
   Standard: Consistent with this level's jfm knowledge-application rubric: "Applies SQL, Python/dbt, and one cloud platform to build transformations within a single domain, consuming established data contracts and governance standards rather than defining them."
   Target:   ⟨target⟩   Due: ⟨date⟩

4. Area: Ensures interoperability with other data products on the mesh by exchanging data through existing well-defined contracts in Parquet, Avro, or Iceberg.  [source: JFM responsibility (P2) — reused, no distinct responsibility content]
   Standard: Consistent with this level's jfm knowledge-application rubric: "Applies SQL, Python/dbt, and one cloud platform to build transformations within a single domain, consuming established data contracts and governance standards rather than defining them."
   Target:   ⟨target⟩   Due: ⟨date⟩

5. Area: Develops working mastery of SQL, Python, and one cloud platform (AWS, GCP, or Azure) through hands-on delivery under defined procedures.  [source: JFM responsibility (P2) — reused, no distinct responsibility content]
   Standard: Consistent with this level's jfm knowledge-application rubric: "Applies SQL, Python/dbt, and one cloud platform to build transformations within a single domain, consuming established data contracts and governance standards rather than defining them."
   Target:   ⟨target⟩   Due: ⟨date⟩

Scorecard

Only perspectives with real canon backing are shown — no Financial or Customer perspective, since nothing in the canon grounds business-financial or customer measures for a role alone.

Internal process

"Writes SQL and dbt transformations that convert raw domain data into final data products compliant with agreed-upon data contracts and governance standards."→ ⟨target⟩ by ⟨date⟩
"Builds, maintains, and evolves domain-specific data modeled as a product within a single domain, consuming established standards rather than authoring them."→ ⟨target⟩ by ⟨date⟩
"Works closely with a Data Product Owner to understand user expectations and translate them into pipeline changes on Snowflake, BigQuery, or Databricks."→ ⟨target⟩ by ⟨date⟩
"Ensures interoperability with other data products on the mesh by exchanging data through existing well-defined contracts in Parquet, Avro, or Iceberg."→ ⟨target⟩ by ⟨date⟩
"Develops working mastery of SQL, Python, and one cloud platform (AWS, GCP, or Azure) through hands-on delivery under defined procedures."→ ⟨target⟩ by ⟨date⟩

Role calibration

Meets the scope bar: "Defined deliverables / small features"→ ⟨target⟩ by ⟨date⟩
Meets the autonomy bar: "General supervision; reviewed at milestones"→ ⟨target⟩ by ⟨date⟩
Meets the complexity bar: "Some non-routine problems; applies established patterns"→ ⟨target⟩ by ⟨date⟩
Meets the impact bar: "Own and immediate-team deliverables"→ ⟨target⟩ by ⟨date⟩
Meets the decision rights bar: "Routine technical choices within guidance"→ ⟨target⟩ by ⟨date⟩
Meets the leadership bar: "May guide interns"→ ⟨target⟩ by ⟨date⟩

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Internal process
  - "Writes SQL and dbt transformations that convert raw domain data into final data products compliant with agreed-upon data contracts and governance standards."  →  ⟨target⟩ by ⟨date⟩   [source: JFM responsibility (P2)]
  - "Builds, maintains, and evolves domain-specific data modeled as a product within a single domain, consuming established standards rather than authoring them."  →  ⟨target⟩ by ⟨date⟩   [source: JFM responsibility (P2)]
  - "Works closely with a Data Product Owner to understand user expectations and translate them into pipeline changes on Snowflake, BigQuery, or Databricks."  →  ⟨target⟩ by ⟨date⟩   [source: JFM responsibility (P2)]
  - "Ensures interoperability with other data products on the mesh by exchanging data through existing well-defined contracts in Parquet, Avro, or Iceberg."  →  ⟨target⟩ by ⟨date⟩   [source: JFM responsibility (P2)]
  - "Develops working mastery of SQL, Python, and one cloud platform (AWS, GCP, or Azure) through hands-on delivery under defined procedures."  →  ⟨target⟩ by ⟨date⟩   [source: JFM responsibility (P2)]

Role calibration
  - Meets the scope bar: "Defined deliverables / small features"  →  ⟨target⟩ by ⟨date⟩   [source: level dimension (Scope)]
  - Meets the autonomy bar: "General supervision; reviewed at milestones"  →  ⟨target⟩ by ⟨date⟩   [source: level dimension (Autonomy)]
  - Meets the complexity bar: "Some non-routine problems; applies established patterns"  →  ⟨target⟩ by ⟨date⟩   [source: level dimension (Complexity)]
  - Meets the impact bar: "Own and immediate-team deliverables"  →  ⟨target⟩ by ⟨date⟩   [source: level dimension (Impact)]
  - Meets the decision rights bar: "Routine technical choices within guidance"  →  ⟨target⟩ by ⟨date⟩   [source: level dimension (Decision rights)]
  - Meets the leadership bar: "May guide interns"  →  ⟨target⟩ by ⟨date⟩   [source: level dimension (Leadership)]