Description

You will design, build, and maintain data pipelines and ETL processes to ingest, transform, and load data from various sources.

This role is hybrid.

Responsibilities

• Build and optimize data architectures and data models to support analytics and reporting needs.
• Develop and maintain data warehouses and data lakes for efficient data storage and retrieval.
• Implement data validation, monitoring, and error-handling mechanisms for reliable data processing.
• Collaborate with data analysts, data scientists, and business stakeholders to deliver data solutions.
• Ensure data quality, integrity, and performance optimization across large datasets.

Required Skills

• 8+ years of experience as a Data Engineer or in a similar role.
• Strong proficiency in Python, Scala, or Java for data processing.
• Hands-on experience with ETL tools such as Informatica, Talend, SSIS, or Apache Airflow.
• Strong experience with SQL and database technologies including SQL Server, PostgreSQL, or Oracle.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Experience with big data technologies like Spark, Hadoop, or Kafka.
• Strong understanding of data warehousing concepts and dimensional modeling.

Preferred Skills

• Experience with Snowflake or Databricks.
• Familiarity with containerization tools such as Docker or Kubernetes.
• Knowledge of data lake architectures and streaming data pipelines.

Key Skills

Education

Bachelor's degree