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