Data Lake / ETL Engineer

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.
  

• 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).
  
  

• 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).
  
  

• 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.