Data Engineer

Key Responsibilities

• Pipeline Development: Design, develop, test, deploy, and maintain batch and near-real-time ETL/ELT pipelines for structured and semi-structured data.
• Orchestration: Build and orchestrate ingestion and transformation workflows using Azure Data Factory and Azure Databricks.
• Data Warehousing: Develop scalable data models, transformations, stored procedures, and performance-optimized workloads in Snowflake.
• Coding & Transformation: Use PySpark, Python, and SQL to cleanse, integrate, validate, and transform data across cloud and enterprise sources.
• Reliability & Monitoring: Implement monitoring, logging, alerting, retry, and error-handling mechanisms to improve pipeline reliability.
• Governance & Security: Apply data-quality checks, reconciliation controls, lineage, documentation, security, and access-control standards.
• Collaboration: Partner with architects, analysts, application teams, and business stakeholders to translate requirements into robust data solutions.
• Operations: Participate in code reviews, CI/CD deployments, production support, root-cause analysis, and continuous optimization.

Required Qualifications

• Education: Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• Experience: 3–5 years of hands-on experience in data engineering, data integration, or cloud data-platform development.
• Core Competencies: Strong experience designing ETL/ELT pipelines and working with dimensional and data-warehouse concepts.
• Snowflake Expertise: Hands-on proficiency including data loading, transformations, query tuning, and warehouse optimization.
• Azure Stack: Practical experience with Azure Data Factory (linked services, datasets, pipelines, triggers, orchestration) and Azure Databricks (Apache Spark/PySpark, notebooks, clusters, Delta Lake concepts).
• Technical Skills: Strong advanced SQL skills and working proficiency in Python; proven experience integrating relational, file, API, and cloud-storage sources.
• Engineering Practices: Understanding of Git-based version control, CI/CD, Agile delivery, and secure cloud data practices.
• Soft Skills: Strong analytical, troubleshooting, communication, and documentation skills.

Preferred Skills

• Azure Data Lake Storage Gen2
• Delta Lake & Snowpipe
• dbt (data build tool)
• Azure DevOps & Git
• REST APIs & Data Governance/Lineage
• Relevant Microsoft Azure or Snowflake certifications