Data Engineering Lead

Coates Group

. Design, build, and lead the evolution of Coates’ next-generation enterprise data platform on AWS .

Posted 9/29/2026full-timeChicago • Illinois • United StatesSenior💰 $145,200 - $165,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and building scalable, cost-efficient AWS data platforms, with a strong focus on data architecture, modeling, and governance. Proficient in implementing production-grade data pipelines and CI/CD practices while providing technical leadership and mentoring to cross-functional teams.

Highest-signal resume keywords

AWS Data EcosystemData Pipeline DevelopmentInfrastructure-as-CodeData Architecture DesignCI/CD Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonSQLData EngineeringData LakeData LakehouseWorkflow OrchestrationDimensional ModelingStreaming TechnologiesProduction SupportTechnical Problem-Solving

Soft Skills

Technical LeadershipDecision-MakingMentoring

Tools & Technologies

AWS S3AWS GlueApache SparkAWS AthenaAWS RedshiftTerraformAWS CDKApache AirflowSnowflakeDatabricks

Industry Keywords

Enterprise Data PlatformData Architecture StandardsOperational Best PracticesGoverned Data ProductsMulti-Cloud Environments

Tech Stack

Tools & technologies

AirflowAmazon RedshiftAWSCloudKafkaPythonSparkSQLTerraform

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

5+ 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
Ability to design scalable, secure, and cost-efficient data architectures
Strong technical problem-solving and decision-making skills
Ability to establish engineering standards, operational best practices, and reliable platform governance processes
Strong understanding of CI/CD pipelines, modern software engineering practices, and production support models
Exposure to streaming technologies such as Kafka or Kinesis, dbt, multi-cloud environments, and/or ML and data science workflows is beneficial

Benefits

Comp & perks

Annual market competitive bonus program
Thrive Program with flexible work options
Dedicated time to prioritize health and wellbeing
Virtual Yoga or meditation sessions
Global Wellness paid day off
Give Back Day
Rapid career advancement opportunities
Equal Opportunity Employer