Senior Data Engineer

Accellor is an AI-first digital transformation partner built for the next generation of enterprise. We help global organizations turn cloud, data, and AI into real, measurable business outcomes at scale.

At Accellor, people come first. You'll be trusted, empowered, and challenged to solve meaningful problems, collaborate with exceptional teams, and continuously grow your skills while building solutions that matter.

Trusted by Fortune 100 companies and global innovators, we work across industries delivering AI solutions, data platforms, and product engineering using modern, scalable technologies. If you want your work to create real impact and shape the future of enterprise, Accellor is where it happens.

We are seeking a Senior Data Engineer to design, build, and optimize scalable data pipelines and cloud-native data platforms. This role will focus heavily on Snowflake data warehousing and AWS-based data pipeline architecture, ensuring high performance, reliability, and security across the data lifecycle.

This is a hands-on technical leadership role ideal for someone who enjoys building modern data systems, mentoring engineers, and driving best practices in data engineering.

• Design, build, and maintain scalable, secure, and high-performance data pipelines in AWS
• Architect and optimize Snowflake data warehouse environments
• Develop and maintain ETL/ELT workflows for structured and semi-structured data
• Implement data modeling best practices (dimensional modeling, star/snowflake schemas)
• Ensure data quality, governance, lineage, and observability
• Optimize performance and cost efficiency across AWS and Snowflake environments
• Collaborate with analytics, data science, and business teams to translate requirements into scalable data solutions
• Implement CI/CD processes for data workflows
• Mentor junior data engineers and establish engineering best practices

• 7+ years of experience in data engineering or related field
• Strong hands-on experience with Snowflake (architecture, performance tuning, RBAC, data sharing, optimization)
• Extensive experience building data pipelines in AWS (e.g., S3, Glue, Lambda, EMR, Redshift, Step Functions, Kinesis)
• Strong SQL expertise and advanced data modeling skills
• Experience with Python (or Scala/Java) for data engineering workflows
• Experience with orchestration tools (Airflow, Prefect, Step Functions, etc.)
• Experience with infrastructure as code (Terraform, Cloud Formation)
• Deep understanding of data warehouse concepts, distributed systems

We strive to offer benefits that support the diverse needs of our employees. Our package includes perks like flexible and discretionary time off, healthcare coverage for you and your loved ones, and a receiving retirement savings plan to help you plan for the future. Additionally, we offer access to flexible spending and health savings accounts, life and AD&D insurance, and opportunities for professional development.