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At Blue Margin, we are on a mission to build the go-to data platform for PE-backed mid-market companies. We are a dynamic, customer-focused company providing hosted data platforms for companies across many industries. We’re passionate about leveraging the power of data to drive business success for our clients. We help mid-market companies turn their data into a strategic asset. Our clients rely on us to design and deliver reporting platforms that fuel better, faster decision-making. We’re passionate about helping clients increase company value through better analysis and decision-making, and we’re looking for a Senior Data Engineer to strengthen our team. As a Senior Data Engineer, you will lead the design, optimization, and scalability of data platforms that power analytics for our clients. You will be hands-on with data pipelines, large-scale data processing, and modern cloud data stacks while mentoring team members and helping shape best practices. This role requires strong expertise in Python (PySpark/Apache Spark), deep knowledge of working with high-volume data, and experience optimizing Delta Lake–based architectures. Exposure to Snowflake or Microsoft Fabric, and tools like Fivetran, Azure Data Factory, and Synapse Pipelines, is highly valued. If you’re motivated by solving complex data challenges, thrive in a collaborative environment, and enjoy applying AI to increase engineering productivity, this role offers the opportunity to have significant technical and strategic impact.
Job Responsibility:
Architect, design, and optimize large-scale data pipelines using tools like PySpark, SparkSQL, Delta Lake, and cloud-native tools
Drive efficiency in incremental/delta data loading, partitioning, and performance tuning
Lead implementations across Azure Synapse, Microsoft Fabric, and/or Snowflake environments
Collaborate with stakeholders and analysts to translate business needs into scalable data solutions
Evaluate and incorporate AI/automation to improve development speed, testing, and data quality
Oversee and mentor junior data engineers, establishing coding standards and best practices
Ensure high standards for data quality, security, and governance
Participate in solution design for client engagements, balancing technical depth with practical outcomes
Requirements:
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
5+ years of professional experience in data engineering, with emphasis on Python & PySpark/Apache Spark
Proven ability to manage large datasets and optimize for speed, scalability, and reliability
Strong SQL skills and understanding of relational and distributed data systems
Experience with Azure Data Factory, Synapse Pipelines, Fivetran, Delta Lake, Microsoft Fabric, or Snowflake
Knowledge of data modeling, orchestration, and Delta/Parquet file management best practices
Familiarity with CI/CD, version control, and DevOps practices for data pipelines
Experience leveraging AI-assisted tools to accelerate engineering workflows
Strong communication skills
ability to convey complex technical details to both engineers and business stakeholders
Nice to have:
Relevant certifications (Azure, Snowflake, or Fabric) a plus
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