Data Engineer

Astronautics Corporation of America•Oak Creek, WI

7d•Hybrid

About The Position

We are seeking a highly skilled and motivated Data Engineer to join our dynamic data team. In this critical role, you will be responsible for designing, building, and maintaining robust, scalable, and efficient data infrastructure and pipelines across our entire data ecosystem. You will transform raw data into high-quality, accessible datasets that empower our data scientists, analysts, and business stakeholders to derive meaningful insights and make data-driven decisions. This hybrid on-site position is located at our headquarters in Oak Creek, WI. You will report directly to the Senior Manager, Business Intelligence.

Requirements

Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field from an accredited institution.
Minimum three years of professional experience in a Data Engineer or similar role, with a strong focus on building scalable data platforms.
Strong proficiency in SQL and expertise in at least one major programming language for data engineering (e.g., Python, Java, Scala). Python is highly preferred.
Hands-on experience with cloud data platforms (e.g., Google Cloud Platform, AWS, Azure), including their core data storage, processing, and orchestration services.
Solid understanding of data warehousing concepts, distributed systems, ETL/ELT and modern data architecture principles.
Familiarity with workflow orchestration tools (e.g., Apache Airflow, Prefect, Dagster).
Strong analytical, problem-solving, and debugging skills.
Excellent communication and collaboration skills, with the ability to articulate complex technical concepts to diverse audiences.

Nice To Haves

Master's degree in a relevant field from an accredited institution.
Experience with specific GCP services (BigQuery, Dataflow, Cloud Storage, Airflow, Cloud Composer, Dataproc, Data Catalog).
Experience with CI/CD concepts via containerization (Docker) and orchestration (Kubernetes).
Knowledge of machine learning concepts and how data engineering supports ML model development and deployment.
Experience with data governance frameworks and tools.
Cration of SDLC/ADLC policies, processes and procedures.

Responsibilities

Design, implement, and optimize scalable data architectures, including data lakes, data warehouses, and streaming platforms, to support current and future analytical and operational needs.
Build, test, and maintain complex ETL/ELT pipelines for both batch and real-time data processing, ensuring data accuracy, consistency, and reliability from source to consumption.
Research, evaluate, and integrate new data technologies, tools, and frameworks (e.g., big data processing engines, cloud services, orchestration tools) to enhance our data platform capabilities.
Continuously monitor and optimize data pipeline performance, scalability, and cost efficiency, ensuring efficient data flow and delivery at scale.
Implement effective data models and manage various data storage solutions (e.g., relational databases, NoSQL databases, object storage).
Implement and enforce data quality checks, validation rules, and security measures to ensure data integrity, privacy, and compliance with organizational policies.
Work closely with data architects, data modeler, BI Specialists, data analysts and business stakeholders to understand data requirements, provide technical guidance, and deliver data solutions that align with business objectives.