Tech Lead, Data Engineering

Coates Group • Chicago, IL

1d • Hybrid

About The Position

Be Part of Our Next Chapter For over almost 60 years, our solutions have enabled impactful connections between some of the world’s leading brands and their customers. And while we’ve already done a lot of work we’re proud of, we’re just getting started! Coates Group has the values of a family-owned business and the innovative spirit of a start-up, both which fuel our purpose – Creating Connections. Empowering Partnerships. Always Evolving . Through hard work, dedication and creativity, we’ve become industry leaders who have won awards and set records while remaining focused on continual growth and evolution. We are a 2x Australia Good Design Award winner and successfully completed the largest hardware deployment in Quick Service Restaurant history. We are curious, charismatic, authentic and we value and leverage the diversity of our crew. We are imaginers, kindness enthusiasts, experts, creators, thinkers, challengers, collaborators and over-achievers. And together, as a Crew, we are revolutionizing the way the world’s leading brands leverage technology to drive the best customer experiences.

Requirements

• 6+ years of experience in data engineering with strong expertise in scalable system and platform design
• Proven experience building, modernizing, or significantly evolving enterprise data platforms and architectures
• Deep hands-on experience within the AWS data ecosystem, including production-scale data lake or lakehouse environments utilizing technologies such as S3, Glue, Spark, Athena, and/or Redshift
• Strong proficiency in Python and SQL with experience developing production-grade data pipelines and transformation workflows
• Experience implementing workflow orchestration solutions, preferably Airflow
• Experience with infrastructure-as-code and automated deployment practices using tools such as Terraform or AWS CDK
• Familiarity with modern data warehousing and lakehouse concepts, including dimensional modeling and platforms such as Snowflake, Redshift, or Databricks

Nice To Haves

• Exposure to streaming technologies (e.g., Kafka or Kinesis), transformation frameworks such as dbt, multi-cloud environments, and/or ML and data science workflows is beneficial

Responsibilities

• Architect and evolve a scalable, cost-efficient AWS data platform that enables enterprise analytics, reporting, and future AI capabilities
• Design and implement reliable, production-grade data pipelines and processing frameworks for batch and near real-time data
• Define enterprise standards for data architecture, modeling, observability, reliability, and platform performance
• Lead foundational technical decisions across tooling, infrastructure, data design, scalability, and operational efficiency
• Implement and maintain infrastructure-as-code, CI/CD pipelines, and automated deployment practices across the data platform
• Enable high-quality, accessible, and governed data products through scalable semantic layers, curated datasets, and transformation standards
• Provide hands-on technical leadership, mentoring, and architectural direction for a growing team of data engineers and cross-functional stakeholders

Benefits

• annual market competitive bonus program
• Thrive Program which includes a suite of flexible work options
• dedicated time to prioritize our health and wellbeing (think virtual Yoga or meditation sessions)
• Global Wellness paid day off to recharge
• Give Back Day to allow our Crew an opportunity to make an impact in the community

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed