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
Required Qualifications
- 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
