Data Engineering Lead
Summary
Lead a team to build and maintain Snowflake-based data ingestion pipelines and AWS data platforms for enterprise clients, enforcing Medallion Architecture and data quality standards.
Job Description
Blendis is hiring a Lead Data Engineer to design and implement scalable ingestion and validation solutions for a leading enterprise client. This client‑facing leadership role requires strong technical expertise in Snowflake-based data platforms, modern data architectures, and AWS, combined with excellent communication skills and a proactive mindset.
Responsibilities
- Lead the design and implementation of data ingestion architectures in Snowflake, ensuring scalability and reliability.
- Own the development of end‑to‑end ELT pipelines integrating multiple data sources.
- Design and enforce data quality frameworks, including validation rules, testing strategies, and monitoring.
- Apply and drive Medallion Architecture (Bronze, Silver, Gold) best practices across data pipelines.
- Build and optimize data pipelines and architectures on AWS (S3, Glue, Lambda, EMR, etc.).
- Develop and enhance data validation and ingestion frameworks, including UI components when needed.
- Act as a technical leader, guiding best practices in data engineering, governance, and pipeline reliability.
- Proactively identify risks, bottlenecks, and data quality issues and implement mitigation strategies.
- Contribute to data governance initiatives, including data definitions, lineage, and stewardship practices.
- Document and continuously improve data platform processes.
Qualifications
- 4+ years of experience in Data Engineering.
- Strong hands‑on experience with Snowflake (Must).
- Experience building ELT pipelines and data ingestion solutions.
- Solid experience with SQL and large‑scale data processing.
- Strong understanding and hands‑on experience with Medallion Architecture (Must).
- Experience building and maintaining data pipelines in AWS (Plus).
- Experience with data quality, validation frameworks, and governance practices.
- Familiarity with Snowflake Cortex (Plus).
- Experience with CI/CD pipelines for data workflows (Plus).
- Experience with Iceberg tables and Snowflake data sharing (Plus).
- Experience with tools such as dbt, Glue, Athena, EMR, Lambda, Terraform, or CloudFormation (Plus).
Key Competencies
- Strong communication skills – ability to work directly with clients and cross‑functional teams.
- Client‑facing mindset – comfortable engaging with stakeholders and driving discussions.
- Proactiveness – ability to anticipate issues and act before they become blockers.
- Ownership & leadership – ability to lead initiatives and influence technical decisions.
- Analytical thinking & problem‑solving.
Benefits
- Learning Opportunities: Certifications in AWS, Databricks, and Snowflake; AI learning paths; study plans and additional certifications tailored to your role; access to Udemy Business; English lessons.
- Travel Opportunities to attend industry conferences and meet clients.
- Mentoring and Development: Career development plans and mentorship programs.
- Celebrations & Support: Special day rewards for birthdays, work anniversaries, and other personal milestones.
- Company‑provided equipment.
- Flexible working options.