Data Lake / ETL Engineer – 4+ Years
Role Overview
We are seeking a Data Lake / ETL Engineer with 4+ 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
o Build and maintain ETL/ELT pipelines for structured and semi-structured
data.
o Support data ingestion from databases, APIs, streaming platforms, and
flat files.
o Ensure data quality, integrity, and lineage across data flows.
Data Lake Engineering
o Assist in the design and development of data lake solutions on cloud and
on-prem.
o Implement storage and retrieval mechanisms optimized for performance.
o Manage metadata and cataloging for discoverability and governance.
Performance & Optimization
o Tune ETL workflows for efficiency and cost-effectiveness.
o Implement partitioning, indexing, and caching for large-scale data
processing.
o Automate repetitive data preparation tasks.
Collaboration & Support
o Work with data scientists and analysts to deliver clean and reliable
datasets.
o Collaborate with senior engineers on best practices for data modeling and
pipeline design.
o Provide L2 support for production pipelines and help troubleshoot failures.
Required Skills & Experience
4+ 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:
o AWS Data Analytics – Specialty / Azure Data Engineer Associate / GCP
Data Engineer.
o dbt or Informatica/Talend certifications.
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