Data Engineer

Description:

We are seeking a Data Engineer to design, build, and maintain scalable data pipelines and infrastructure that support analytics, reporting, and data-driven decision making. This role will also play a key part in establishing and enforcing data governance standards to ensure data is accurate, secure, and trusted across the organization.

Key Responsibilities

• Design, develop, and maintain robust ETL/ELT pipelines to ingest, transform, and load data from various sources
• Build and optimize data models to support analytics and reporting use cases
• Ensure data quality, integrity, and reliability through monitoring, validation, and testing
• Implement and support data governance practices, including data lineage, cataloging, and metadata management
• Enforce data standards, naming conventions, and access controls across datasets
• Partner with business stakeholders to define data ownership, definitions, and quality expectations
• Manage and optimize data storage solutions (data warehouses, lakes, lakehouses)
• Implement performance tuning and cost optimization strategies
• Maintain documentation for data architecture, pipelines, and governance processes
• Support deployment and orchestration of data workflows using modern tools
• Troubleshoot and resolve data issues in a timely manner

Requirements:

• Bachelor’s degree in Computer Science, Information Systems, or related field (or equivalent experience)
• 2–5+ years of experience in data engineering or related roles
• Strong SQL skills and experience working with relational databases
• Experience building data pipelines using tools such as Python, Spark, or similar
• Familiarity with cloud platforms (Azure, AWS, or GCP)
• Experience with data warehousing technologies (e.g., Snowflake, BigQuery, Redshift, or Fabric)
• Understanding of data modeling concepts (star schema, normalization, etc.)
• Experience supporting or working within data governance frameworks (data quality, lineage, access control, or catalog tools)

Preferred Qualifications:

• Experience with orchestration tools (Airflow, Azure Data Factory, etc.)
• Knowledge of real-time/streaming data processing
• Familiarity with DevOps practices (CI/CD, version control)
• Experience working in a lakehouse architecture (e.g., Delta Lake, Microsoft Fabric)
• Experience with data governance tools (e.g., Microsoft Purview, Collibra, Alation)
• Strong understanding of data security and compliance best practices
• Strong problem-solving and communication skills