Design, build, and maintain scalable and efficient data pipelines for ingesting and transforming data from multiple sources.
Develop and manage cloud-based data lakes optimized for analytics and business intelligence usage.
Work closely with data science and BI teams to understand data requirements and ensure seamless integration of datasets.
Implement and maintain data quality checks, data profiling, and monitoring mechanisms.
Establish and enforcedata governance policies including data lineage, cataloging, and access control.
Optimize data processing workloads for performance and cost-efficiency in cloud environments.
Collaborate across teams to understand evolving data needs and improve data infrastructure accordingly.
Technical and Functional Skills:
BE or B.Tech graduate with 5+ years of experience in Data Engineering.
Proficient in SQL and Python for data manipulation and ETL development.
Experience with ETL tools such as Alteryx, Tableau Prep, Apache Airflow, or similar.
Strong hands-on experience with cloud platforms like Azure (especially services like S3, BigQuery, Redshift, Glue, Dataflow, or equivalent), AWS, GCP.
Experience with data lake architecture and file formats like Parquet, Avro, or Delta Lake.
Working knowledge of data quality and observability tools like Great Expectations or Monte Carlo (Good to have).
Familiarity with metadata management, data cataloging, and governance frameworks.
Ability to design data models, understand business needs, and translate them into efficient data workflows.
Experience with Tableau, Power BI, Looker for downstream BI integration and data integrity testing.
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Data Science & AnalyticsRole Category: Business Intelligence & AnalyticsRole: Data AnalystEmployement Type: Full time