Senior Data Engineer

Position Summary

We are seeking a Senior Data Engineer to design, build, and optimize scalable data infrastructure that powers business intelligence, analytics, and AI-driven applications. The ideal candidate brings great communication skills, deep expertise in Python, containerization, cloud-native architectures, and modern data warehousing, with a growing interest in AI agents and emerging integration patterns.

What you will do:

Data Infrastructure & Pipeline Development

• Design and implement robust, scalable ETL/ELT pipelines to ingest, transform, and deliver data across the organization

• Build and maintain data models optimized for analytical workloads and downstream consumption

• Develop reusable frameworks and libraries to accelerate data engineering workflows

Cloud & Platform Engineering

• Architect and manage cloud-native data solutions on AWS, leveraging services such as S3, EC2, ECS, ECR and EventBridge

• Deploy and orchestrate containerized workloads using Docker and Kubernetes in production environments

• Implement infrastructure-as-code practices using Terraform, CloudFormation, or similar tools

Data Warehousing

• Design and optimize data warehouse architectures using Redshift or Snowflake

• Develop efficient data models, partitioning strategies, and query optimization techniques

• Manage data lifecycle, governance, and cost optimization within warehouse environments

Emerging Technologies

• Explore and integrate AI agents and Model Context Protocol (MCP) patterns into data workflows where applicable

• Collaborate with AI/ML teams to ensure data infrastructure supports model training, inference, and feature engineering needs

• Stay current with emerging data and AI technologies, evaluating their potential business impact

Collaboration & Leadership

• Partner with analytics, product, and engineering teams to understand data requirements and deliver solutions

• Mentor junior engineers and contribute to team best practices, code reviews, and technical documentation

• Participate in architectural decisions and contribute to the data platform roadmap

What you will need:

Experience

• 7+ years of professional experience in data engineering or related roles

• Proven track record building and operating production data pipelines at scale

Technical Skills

• Python: Advanced proficiency including data libraries (pandas, PySpark, SQLAlchemy), testing frameworks, and packaging

• Containerization & Orchestration: Strong hands-on experience with Docker and Kubernetes (EKS, GKE, or self-managed clusters)

• Data Warehousing: Deep expertise with Redshift or Snowflake, including performance tuning, data modeling, and administration including DBT

• AWS: Extensive experience across the AWS ecosystem, particularly data-related services (S3, Glue, Lambda, IAM, VPC, CloudWatch)

• SQL: Expert-level SQL skills for complex analytical queries and data transformations

Foundational Skills

• Experience with workflow orchestration tools (Airflow, Dagster, etc.)

• Familiarity with version control (Git), CI/CD pipelines, and agile development practices

• Strong understanding of data governance, security, and compliance principles

Preferred Qualifications: