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Data Lake / ETL Engineer

Whitefield Careers
Full Timejunior
Posted March 10, 2026

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Job Description

Data Lake / ETL Engineer - 2+ Years

Role Overview

We are seeking a Data Lake / ETL Engineer with 2+ years of experience in designing, developing, and maintaining data pipelines and ETL/ELT processes. The role focuses on building and optimizing data ingestion, transformation, and storage solutions that enable business analytics, AI/ML use cases, and secure enterprise data lakes.

Key Responsibilities

  • Pipeline Development
  • * Build and maintain ETL/ELT pipelines for structured and semi-structured data.
  • Support data ingestion from databases, APIs, streaming platforms, and flat files.
  • Ensure data quality, integrity, and lineage across data flows.
  • Data Lake Engineering
  • * Assist in the design and development of data lake solutions on cloud and on-prem.
  • Implement storage and retrieval mechanisms optimized for performance.
  • Manage metadata and cataloging for discoverability and governance.
  • Performance & Optimization
  • * Tune ETL workflows for efficiency and cost-effectiveness.
  • Implement partitioning, indexing, and caching for large-scale data processing.
  • Automate repetitive data preparation tasks.
  • Collaboration & Support
  • * Work with data scientists and analysts to deliver clean and reliable datasets.
  • Collaborate with senior engineers on best practices for data modeling and pipeline design.
  • Provide L2 support for production pipelines and help troubleshoot failures.

Required Skills & Experience

  • 2+ years of experience in data engineering or ETL development.
  • Proficiency in SQL and Python (or Scala/Java) for data transformations.
  • Hands-on with ETL tools (Informatica, Talend, dbt, SSIS, Glue, or similar).
  • Exposure to big data technologies (Hadoop, Spark, Hive, Delta Lake).
  • Familiarity with cloud data platforms (AWS Glue/Redshift, Azure Data Factory/Synapse, GCP Dataflow/BigQuery).Understanding of workflow orchestration (Airflow, Oozie, Prefect, or Temporal).
  • Preferred Knowledge
  • Experience with real-time data pipelines using Kafka, Kinesis, or Pub/Sub.
  • Basic understanding of data warehousing and dimensional modeling.
  • Exposure to containerization and CI/CD pipelines for data engineering.Knowledge of data security practices (masking, encryption, RBAC).
  • Education & Certifications
  • Bachelor's degree in Computer Science, IT, or related field.
  • Preferred certifications:
  • * AWS Data Analytics - Specialty / Azure Data Engineer Associate / GCP Data Engineer.
  • dbt or Informatica/Talend certifications.

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