Lead 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

6-10 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 6 years of hands-on experience with Snowflake or modern cloud data warehouse

Minimum 3 years of hands-on experience in data modeling

Minimum 2 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