Gig Engineer provides fast access to a global pool of engineers for on-demand project work. It is an AI-driven project delivery platform designed for engineering work, connecting full-time,…
Gig Engineer provides fast access to a global pool of engineers for on-demand project work. It is an AI-driven project delivery platform designed for engineering work, connecting full-time,…
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Overview of the Role:
The ETL Engineer is responsible for designing, developing, maintaining, and optimizing. Extract, Transform, Load (ETL) pipelines that support enterprise data integration, analytics,
reporting, and operational requirements. The ideal candidate has strong technical skills in
data engineering, SQL, and ETL tools, with an understanding of data modelling,
governance, and best practices in data processing. The role ensures high-quality, accurate,
and reliable data delivery for business and analytical use.
RESPONSIBLE FOR: -
ETL Development & Pipeline Engineering
Design, build, and optimize ETL/ELT workflows for structured and unstructured datasets.
Develop data pipelines for ingestion, transformation, and loading into data warehouses or data lakes.
Write efficient SQL queries, transformations, stored procedures, and data scripts.
Implement incremental loads, change-data-capture (CDC), and automated data processes.
Data Integration
Integrate data from multiple internal and external systems (APIs, DBs, files, applications).
Seamlessly connect ETL pipelines to cloud storage, relational databases, streaming sources, or third-party platforms.
Handle data profiling, cleansing, mapping, and validation.
Data Quality & Validation
Develop data quality rules, validation checks, reconciliation processes, and exception handling.
Monitor data pipelines and resolve issues proactively.
Ensure accuracy, completeness, and consistency of all processed data.
Data Architecture & Modelling Support
Collaborate with data architects to design scalable data models and ETL frameworks.
Implement SCD (Slowly Changing Dimensions), fact and dimension design, and OLAP/OLTP optimizations.
Contribute to data governance, metadata management, and documentation standards.
Automation, Scheduling & Performance
Automate workflows using schedulers (Airflow, ADF, Control-M, etc.).
