Job Summary

We are looking for an experienced ETL Data Engineer to design, develop, and maintain scalable ETL pipelines that support data integration, transformation, and reporting. The ideal candidate should have strong experience in SQL, data warehousing, cloud platforms, and ETL tools, with the ability to work closely with business stakeholders and cross-functional teams.

Key Responsibilities

• Design, develop, and maintain ETL/ELT pipelines for data integration.
• Extract, transform, and load data from multiple source systems into data warehouses or data lakes.
• Develop and optimize SQL queries, stored procedures, and database objects.
• Build scalable and efficient data pipelines for structured and unstructured data.
• Perform data validation, cleansing, and quality checks.
• Troubleshoot ETL failures and optimize job performance.
• Collaborate with Data Analysts, BI Developers, and Business Teams to understand reporting requirements.
• Ensure data integrity, security, and governance standards are maintained.
• Automate ETL workflows and scheduling using enterprise scheduling tools.
• Monitor ETL jobs and resolve production issues promptly.
• Create technical documentation for ETL processes and data mappings.
• Participate in code reviews and follow best development practices.

Required Skills

• Strong experience with ETL tools such as:
  • Informatica PowerCenter
  • SSIS
  • Talend
  • Pentaho
  • DataStage
  • Matillion
  • Azure Data Factory (ADF)
• Strong SQL skills
• Data Warehousing concepts (Star Schema, Snowflake Schema)
• Data Modeling
• Database experience with SQL Server, Oracle, PostgreSQL, MySQL, or Snowflake
• Experience with Python for data processing (preferred)
• Knowledge of Unix/Linux shell scripting
• Experience with Git or other version control tools
• Experience with scheduling tools like Control-M, Autosys, or Airflow

Cloud (Preferred)

Experience with one or more cloud platforms:

• Microsoft Azure
• AWS
• Google Cloud Platform (GCP)

Relevant cloud services include:

• Azure Data Factory
• Azure Synapse Analytics
• AWS Glue
• AWS Redshift
• Amazon S3
• Google BigQuery
• Google Cloud Dataflow

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• 10+ years of hands-on experience in ETL development and data engineering.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration abilities.

Preferred Qualifications

• Experience with Big Data technologies (Spark, Hadoop, Kafka)
• Knowledge of CI/CD pipelines
• Experience with Power BI, Tableau, or other BI tools
• Azure Data Engineer, AWS Data Analytics, or Snowflake certifications are a plus.

Nice-to-Have Skills

• Python
• PySpark
• Apache Spark
• Snowflake
• Databricks
• Airflow
• Docker
• Kubernetes
• REST APIs
• Agile/Scrum methodology