1.
Data Engineering & Pipeline Development
Develop and maintain data pipelines across the medallion lifecycle:
Bronze : raw data ingestion
Silver : cleaned/transformed data
Gold : consumption‐ready data for analytics/BI
Build scalable, reliable, and secure pipelines using
Spark ,
Databricks , or similar frameworks.
Implement
DataOps
practices, Infrastructure‐as‐Code, and observability solutions to ensure smooth data operations.
2.
Data Modeling & Architecture
Develop data models using best practices such as
Data Vault 2.0 ,
Kimball , etc.
Co‐develop master and reference data tables, ensuring alignment with enterprise data governance standards.
Support mapping of the Data Estate, covering multiple functions like HR, Finance, Product, Infrastructure, etc.
3.
Data Governance & Quality
Implement and enforce data governance policies, including access control and security for sensitive data.
Co‐develop data quality pipelines to monitor and remediate issues in collaboration with domain data owners and stewards.
Publish curated data assets on the data catalog for organizational use.
4.
Platform Reliability & Security
Ensure the reliability and security of the Data Platform to minimize downtime for critical data products.
Serve as a subject‐matter expert (SME) on the platform stack: Databricks, Tableau, MicroStrategy, and similar technologies.
Conduct feasibility assessments, POCs, and production rollouts of industry‐leading tools (e.g., dbt, Neo4j, Fivetran, Apache Atlas).
5.
Advisory & Collaboration
Provide expert guidance on building, maintaining, and optimizing data pipelines.
Develop domain‐specific expertise in various functions and support cross‐functional data initiatives.
Collaborate closely with the data governance team, analytics teams, and business stakeholders to drive adoption of best practices.
Must‐Have Skills / Experience
Data Engineering & Pipelines
Experience with
Spark
and
Databricks
for building and maintaining data pipelines.
Knowledge of medallion architecture (Bronze → Silver → Gold).
Hands‐on with ETL/ELT processes and
DataOps
practices.
Data Modeling & Architecture
Experience with
Data Vault 2.0 ,
Kimball , or other data modeling frameworks.
Ability to design and maintain master and reference data tables.
Data Governance & Quality
Familiarity with data governance policies, access control, and security best practices.
Experience building or supporting data quality pipelines.
Ability to publish curated datasets to a data catalog.
Platform & Tool Expertise
Experience with BI tools: Tableau, MicroStrategy.
Knowledge of data management or orchestration tools: dbt, Apache Atlas, Fivetran.
Soft Skills & Collaboration
Able to advise and mentor colleagues on data pipeline best practices.
Strong communication skills and ability to collaborate across multiple teams and business domains.
Nice‐to‐Have / Bonus Skills
Exposure to Infrastructure‐as‐Code, monitoring, and observability for data platforms.
Experience in public sector data initiatives.
Domain expertise in HR, Finance, Product, or Infrastructure datasets.
Conducting feasibility assessments, POCs, or production rollouts for enterprise‐grade data tools.
Knowledge of security and reliability best practices for critical data products.
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