Data Engineer

Duties & Responsibilities:

• Lead the design, development, and optimization of ETL/ELT pipelines and workflows
• Write, tune, and optimize advanced SQL queries for large-scale data processing
• Build and maintain data warehouses and data models (relational, dimensional, star schema)
• Translate business requirements into robust, well-architected, and reusable data solutions
• Partner with analysts, data scientists, and stakeholders to deliver trusted, actionable datasets
• Implement and maintain unit tests, integration tests, and validation frameworks to ensure pipeline reliability
• Document workflows, and design decisions to support knowledge sharing and operational continuity
• Apply coding standards, CI/CD practices, version control, and peer code reviews to ensure high-quality deliverables
• Proactively monitor, optimize, and troubleshoot pipelines for performance, scalability, and cost efficiency
• Support deployments and handle post-production monitoring and incident resolution
• Mentor associate engineers, providing technical guidance and feedback

Requirements

Basic Qualifications:

• Bachelor’s degree in computer science, Information Systems, Engineering, or a related field
• 4–7 years of hands-on experience in data engineering or related fields
• Expertise in writing complex SQL queries, optimizing, using advanced functionals and turning the performance on cloud data warehouse environment.
• Strong experience with data warehousing concepts, design, and implementation
• Minimum 3 years of hands-on experience with Snowflake or modern cloud data warehouse
• Minimum 2 years of hands-on experience in data modeling
• Minimum 1 year of hands-on Python development (ETL/ELT scripting, OOP, automation)
• Strong knowledge of at least one major cloud platform (AWS, Azure, or GCP)
• Experience with orchestration tools (e.g., Airflow, ADF, Luigi) for workflow management
• Demonstrated ability to lead and mentor teams while managing multiple priorities
• Strong communication and stakeholder management skills
• Strong hands-on experience with data warehousing concepts, design, and implementation

Preferred Qualifications:

• Hands-on experience with DBT (Data Build Tool) for data transformations
• Familiarity with DevOps and CI/CD best practices in data engineering
• Exposure with real-time/streaming platforms (Kafka, Spark Streaming, Flink)
• Exposure to the e-commerce domain or large-scale B2B/B2C environments
• Has the ability to break down problems and estimate time for development tasks
• Experience mentoring and guiding junior engineers
• Understands the technology landscape, up to date on current technology trends and new technology, brings new ideas to the team
• Learns organization vision statement and decision-making framework. Able to understand how team and personal goals/objectives contribute to the organization vision