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Senior Data Engineer- Remote, India ( r

Remote / Online - Candidates ideally in
Los Angeles, Los Angeles County, California, 90079, USA
Listing for: Leewayhertz Technologies
Remote/Work from Home position
Listed on 2026-10-03
Job specializations:
  • IT/Tech
    Data Engineering, Data Warehousing
Salary/Wage Range or Industry Benchmark: 140000 - 180000 USD Yearly USD 140000.00 180000.00 YEAR
Job Description & How to Apply Below
Position: Senior Data Engineer- Remote, India ( Immediate Joiner)

Role & responsibilities

  • Design, develop, and maintain scalable data pipelines for data ingestion, processing and storage.
  • Build and optimize data architectures and data models (Lakehouse / medallion, dimensional) for efficient data storage and retrieval.
  • Develop ETL/ELT processes to transform and load data from various sources into data warehouses and data lakes.
  • Build and orchestrate pipelines on Azure Databricks using PySpark, Spark SQL and Delta Lake, orchestrated with Databricks Workflows.
  • Integrate data from enterprise source systems including SAP (ABAP/CDS extracts, RPA/CSV or connectors) and load into Snowflake and Databricks.
  • Own end-to-end CI/CD for data pipelines using Databricks Asset Bundles (DAB) and Azure Dev Ops (Git repositories, YAML build and release pipelines), promoting code across dev, QA and production.
  • Implement data quality, validation, freshness and reconciliation checks with pipeline observability.
  • Ensure data integrity, quality, and security across all data systems.
  • Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions that meet business needs.
  • Monitor and troubleshoot data pipelines and workflows to ensure high availability and performance.
  • Document data processes, architectures, and data flow diagrams.
Preferred candidate profile
  • 7 - 8 years of hands-on data engineering experience building and running production data pipelines at scale.
  • Strong expertise in Azure and Azure data services (ADLS Gen2, Azure Databricks, Azure Dev Ops).
  • Deep hands-on experience with Databricks:
    PySpark, Spark SQL, Delta Lake, Lakehouse / medallion architecture and Databricks Workflows.
  • CI/CD for data engineering using Databricks Asset Bundles (DAB) and Azure Dev Ops (Git, YAML build/release pipelines, multi-environment promotion). (Must-have)
  • Strong Snowflake experience (data modeling, performance tuning, loading and optimization).
  • Proficiency in SQL and Python.
  • Experience integrating data from SAP and other enterprise ERP / source systems into a data lake or warehouse.
  • Solid data modeling (dimensional, star/snowflake, Lakehouse) and ETL/ELT design.
  • Building data-quality, validation, reconciliation and pipeline monitoring / observability.
Position Requirements
10+ Years work experience
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