Senior Data Engineer
- Leewayhertz
- 7 - 12 years
- Noida, Gurugram
- 12 days ago
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Job Description
Job Description
We are seeking a highly skilled Senior Data Engineer with deep expertise in AWS data services, data wrangling using Python & PySpark, and a solid understanding of data governance, lineage, and quality frameworks. The ideal candidate will have a proven track record of delivering end-to-end data pipelines for logistics, supply chain, enterprise finance, or B2B analytics use cases.
Role & responsibilities
- Design, build, and optimize ETL pipelines using AWS Glue 3.0+ and PySpark.
- Implement scalable and secure data lakes using Amazon S3, following bronze/silver/gold zoning.
- Write performant SQL using AWS Athena (Presto) with CTEs, window functions, and aggregations.
- Take full ownership from ingestion transformation validation metadata documentation dashboard-ready output.
- Build pipelines that are not just performant, but audit-ready and metadata-rich from the first version.
- Integrate classification tags and ownership metadata into all columns using AWS Glue Catalog tagging conventions.
- Ensure no pipeline moves to QA or BI team without validation logs and field-level metadata completed.
- Develop job orchestration workflows using AWS Step Functions integrated with EventBridge or CloudWatch.
- Manage schemas and metadata using AWS Glue Data Catalog.
- Take full ownership from ingestion transformation validation metadata documentation dashboard-ready output.
- Ensure no pipeline moves to QA or BI team without validation logs and field-level metadata completed.
- Enforce data quality using Great Expectations, with checks for null %, ranges, and referential rules.
- Ensure data lineage with OpenMetadata or Amundsen and add metadata classifications (e.g., PII, KPIs).
- Collaborate with data scientists on ML pipelines, handling JSON/Parquet I/O and feature engineering.
- Must understand how to prepare flattened, filterable datasets for BI tools like Sigma, Power BI, or Tableau.
- Interpret business metrics such as forecasted revenue, margin trends, occupancy/utilization, and volatility.
- Work with consultants, QA, and business teams to finalize KPIs and logic.
- Build pipelines that are not just performant, but audit-ready and metadata-rich from the first version.
- Integrate classification tags and ownership metadata into all columns using AWS Glue Catalog tagging conventions.
Preferred candidate profile
- Strong hands-on experience with AWS: Glue, S3, Athena, Step Functions, EventBridge, CloudWatch, Glue Data Catalog.
- Programming skills in Python 3.x, PySpark, and SQL (Athena/Presto).
- Proficient with Pandas and NumPy for data wrangling, feature extraction, and time series slicing.
- Strong command over data governance tools like Great Expectations, OpenMetadata / Amundsen.
- Familiarity with tagging sensitive metadata (PII, KPIs, model inputs).
- Capable of creating audit logs for QA and rejected data.
- Experience in feature engineering rolling averages, deltas, and time-window tagging.
BI-readiness with Sigma, with exposure to Power BI / Tableau (nice to have).
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Production, Manufacturing & EngineeringRole Category: EngineeringRole: Engineering - OtherEmployement Type: Full timeContact Details:
Company: LeewayhertzLocation(s): Noida, Gurugram
Keyskills: AWS Data Ingestion Pyspark Data Quality Data Lineage Metadata Management Redshift Aws Metadata Great Expectation Aws Glue Data Governance Python
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