Senior Data Engineer at Accellor designing and optimizing scalable data pipelines with a strong focus on Snowflake and AWS. Leading technical initiatives and mentoring engineers for best practices in data engineering.
Responsibilities
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
Requirements
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, CloudFormation)
Deep understanding of data warehouse concepts, distributed systems
Benefits
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.
Receiving retirement savings plan to help you plan for the future.
Access to flexible spending and health savings accounts.
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