Lead Data Engineer

Position:
Lead Data Engineer

Location:

Mumbai

Experience:

10+ years

5 Years into DBT, Snowflake and Airbyte or Airbyte Alternatives

Designing, building, and maintaining data pipelines using cloud technologies to

ensure efficient data flow and quality for analysis by data scientists and business

users.

Key Responsibilities .

• Data ingestion and extraction:
Utilize Airbyte to establish connections to

various data sources, configure data extraction pipelines, and manage data

replication schedules.

• Data transformation with dbt:
Write dbt models to clean, transform, and

aggregate data according to business requirements, leveraging dbt's declarative

syntax for maintainable data pipelines.

• Snowflake data modeling:
Design and implement data models in Snowflake,

optimizing for performance and query efficiency, including dimensional

modeling techniques.

• Pipeline monitoring and maintenance:
Monitor data pipelines for errors,

troubleshoot issues, and implement alerts to ensure data quality and reliability.

• Data quality checks:
Implement data validation processes to identify and

address data inconsistencies or errors before loading into Snowflake.

• Collaboration with stakeholders:
Work closely with data analysts, data

scientists, and business teams to understand data needs, define data

requirements, and deliver actionable insights.

Required skills:

• Knowledge of ETL/ELT processes, data modelling, data quality best

practices, and change data capture (CDC).

• SQL - Strong SQL skills to query, manipulate, and transform data

• Airbyte - Understanding of Airbyte connectors, configuration, and data

synchronization capabilities.

• dbt - Familiarity with dbt syntax, development workflow, and best practices

for data transformation.

• Snowflake - Understanding of Snowflake architecture, data warehousing

concepts, and performance optimization techniques.

• Cloud computing skills - Familiarity with cloud platforms like AWS, Azure.