Data Engineer, Aladdin Data, Associate
BlackRock · Mumbai · 5+ yrs experience · Posted 2026-07-18
Tech stack: Azure, Kafka, Python, SQL
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About the role
About this role Overview The Associate - Data Platform Engineer engages in projects from the start, including: Refining requirements Designing, developing, testing, deploying, and maintaining Enterprise Data Platform (EDP) enabling core framework components Key tasks include: Automating data pipelines Supporting teams using the framework Adhering to data platform standards Enhancing performance and scalability Responsibilities
Responsibilities:
- Actively participate in chapter ceremony meetings and contribute to project planning and estimation
- Coordinate work with product managers, data owners, platform teams, and other stakeholders throughout the SDLC cycle
- Use Airflow, Python, Snowflake, dbt, and related technologies to enhance and maintain EDP acquisition, ingestion, processing, orchestration and DQ frameworks
- Adopt new tools and technologies to enhance framework capabilities
- Build and conduct end-to-end tests to ensure production operations run successfully after every release cycle
- Document and present accomplishments and challenges to internal and external stakeholders
- Demonstrate deep understanding of modern data engineering tools and best practices
- Design and build solutions which are performant, consistent, and scalable
- Contribute to design decisions for complex systems
- Provide L2 / L3 support for technical and/or operational issues
Qualifications:
- At least 5+ years' experience as a data engineer
- Expertise with SQL, stored procedures, UDFs
- Advanced level Python programming
- Experience with Snowflake or similar cloud native databases
- Experience with orchestration tools, especially Airflow
- Experience with declarative transformation tools like dbt
- Experience in Azure services, especially ADLS (or equivalent)
- Exposure to real time streaming platforms and message brokers (e.g., Snowpipe Streaming, Kafka)
- Experience with Agile development concepts and related tools (ADO, Aha)
- Experience conducting root cause analysis and solve issues
- Experience with performance tuning
- Excellent written and verbal communication skills
- Ability to operate in a matrixed organization and fast-paced environment
- Strong interpersonal skills with a can-do attitude under challenging circumstances
- Bachelor's degree in computer science is strongly preferred
Qualifications
- At least 5+ years' experience as a data engineer
- Expertise with SQL, stored procedures, UDFs
- Advanced level Python programming
- Experience with Snowflake or similar cloud native databases
- Experience with orchestration tools, especially Airflow
- Experience with declarative transformation tools like dbt
- Experience in Azure services, especially ADLS (or equivalent)
- Exposure to real time streaming platforms and message brokers (e.g., Snowpipe Streaming, Kafka)
- Experience with Agile development concepts and related tools (ADO, Aha)
- Experience conducting root cause analysis and solve issues
- Experience with performance tuning
- Excellent written and verbal communication skills
- Ability to operate in a matrixed organization and fast-paced environment
- Strong interpersonal skills with a can-do attitude under challenging circumstances
- Bachelor's degree in computer science is strongly preferred
Responsibilities
- Actively participate in chapter ceremony meetings and contribute to project planning and estimation
- Coordinate work with product managers, data owners, platform teams, and other stakeholders throughout the SDLC cycle
- Use Airflow, Python, Snowflake, dbt, and related technologies to enhance and maintain EDP acquisition, ingestion, processing, orchestration and DQ frameworks
- Adopt new tools and technologies to enhance framework capabilities
- Build and conduct end-to-end tests to ensure production operations run successfully after every release cycle
- Document and present accomplishments and challenges to internal and external stakeholders
- Demonstrate deep understanding of modern data engineering tools and best practices
- Design and build solutions which are performant, consistent, and scalable
- Contribute to design decisions for complex systems
- Provide L2 / L3 support for technical and/or operational issues
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