Tech Lead, Data Engineering

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 Qualifications Ability to design scalable, secure, and cost‑efficient data architectures that support enterprise analytics and future AI initiatives Strong technical problem‑solving and decision‑making skills, including balancing trade‑offs between scalability, complexity, performance, and cost 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 Experience enabling accessible, high‑quality data products for analytics, reporting, and downstream business consumers Ability to work collaboratively across technical and business stakeholders while providing hands‑on technical leadership and direction 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 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 Benefits The benefits include an annual market competitive bonus program and our Thrive Program which includes a suite of flexible work options because we’re strong believers that you should never miss an important life or work moment. Thrive also provides dedicated time to prioritize our health and wellbeing (virtual yoga or meditation sessions), a Global Wellness paid day off to recharge as well as a Give Back Day to allow our Crew an opportunity to make an impact in the community. Equal Opportunity Employer Coates Group is an Equal Opportunity Employer and does not discriminate on the basis of race, color, creed, national or ethnic origin, gender, religion, disability, age, political affiliation or belief, disabled veteran, veteran of the Vietnam Era, or citizenship status (except in those special circumstances permitted or mandated by law). #J-18808-Ljbffr Coatesgroup