Job Title: Data Engineer
Job Description
This role combines data engineering and applied data science to design, build, and maintain large-scale data pipelines for time series datasets using Databricks or comparable big data platforms. You will focus on creating scalable, reliable data architectures and pipelines that power high-quality analytics and enable seamless integration of AI and machine learning workloads. The position is engineering-first, but also involves building and deploying machine learning models to support forecasting, anomaly detection, and pattern recognition, particularly for vehicle test data in an automotive product development or manufacturing environment. You will work closely with product and engineering teams to turn complex data into trusted, production-ready data assets and actionable insights.
Responsibilities
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Design, develop, and maintain scalable data pipelines using Databricks, PySpark, and cloud-native tools to ingest, clean, and transform large time series datasets.
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Explore, evaluate, and implement new tools and techniques to improve data processing, modeling, and automation across the data lifecycle.
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Design and maintain data models optimized for analytical and machine learning workloads, with a particular focus on time series data.
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Build, train, and evaluate machine learning models for forecasting, anomaly detection, and pattern recognition in time series datasets.
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Create analysis modules for vehicle test data and ensure they meet the needs of automotive product development or manufacturing use cases.
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Collaborate closely with cross-functional engineering and product teams to understand data needs, define requirements, and deliver high-quality analytical solutions.
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Constantly communicate with engineering teams to understand mechanics, electrical, and controls problems and translate them into data-driven analyses.
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Optimize Spark and other distributed data processing jobs for performance, reliability, and cost efficiency.
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Implement and uphold best practices for data quality, including validation, monitoring, and data governance.
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Establish and maintain robust versioning, testing, and documentation practices for data pipelines, models, and analytics assets.
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Build and maintain ETL/ELT pipelines in cloud environments to support both batch and potentially streaming data workloads.
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Apply machine learning fundamentals to real-world datasets and integrate models into production data pipelines.
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Translate complex technical and analytical findings into clear, actionable business insights for technical and non-technical stakeholders.
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Contribute to shaping the overall data strategy and architecture for high-impact analytical products and solutions.
Essential Skills
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3+ years of experience in data engineering, data science, or a hybrid data engineering/data science role.
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Strong proficiency with Databricks or comparable big data platforms (such as Snowflake, Amazon Redshift, or other Spark-based or cloud-native analytics frameworks).
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Hands-on experience with PySpark and distributed data processing for large-scale datasets.
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Experience building and maintaining ETL/ELT pipelines in a cloud environment such as Azure, AWS, or GCP.
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Hands-on experience working with time series data, including feature engineering, forecasting, and anomaly detection.
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Strong programming skills in Python with professional experience, including 1–5 years working with Python in an automotive environment.
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Familiarity with common data science libraries such as pandas, NumPy, and scikit-learn.
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Experience with MLflow, Delta Lake, or Databricks AutoML for managing experiments, models, and data.
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Strong SQL skills and experience working with large relational or NoSQL databases.
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Understanding of machine learning fundamentals and experience applying models to real-world datasets.
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Ability to translate complex technical concepts and analytical results into clear business insights.
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Strong communication and collaboration skills to work effectively with cross-functional teams.
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Curiosity, an ownership mindset, and a willingness to explore new tools, techniques, and approaches.
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Comfort working in a fast-paced, iterative environment with evolving requirements.
Additional Skills & Qualifications
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Experience in an automotive product development or manufacturing environment, particularly working with vehicle test data.
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Experience creating analysis modules for vehicle test data and supporting engineering teams focused on mechanics, electrical, and controls.
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Familiarity with streaming data technologies such as Structured Streaming, Kinesis, or similar frameworks.
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Background in MLOps, including CI/CD for data pipelines and productionizing machine learning models.
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Experience with data visualization tools such as Power BI, Tableau, or similar platforms.
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Knowledge of statistics, experimental design, or causal inference to support robust analytical conclusions.
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Experience implementing new tools and techniques to enhance data processing, modeling, and automation.
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Exposure to cloud-native analytics frameworks and modern data architectures using tools like Delta Lake and AutoML.
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Interest in shaping data strategy and architecture for high-impact analytical products.
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Motivation to work in a collaborative team environment that values experimentation, learning, and technical excellence.
Work Environment
This position is based onsite in the Detroit, MI (Redford) area. You will work closely with engineering and product teams in an automotive-focused environment, collaborating frequently to understand vehicle test data and related mechanics, electrical, and controls challenges. The role involves extensive use of Databricks, PySpark, cloud platforms (such as Azure, AWS, or GCP), and modern data and machine learning tooling including MLflow, Delta Lake, and AutoML. The team culture emphasizes collaboration, experimentation, continuous learning, and technical excellence, with opportunities to shape the data strategy and architecture for high-impact analytical products. The organization offers competitive compensation, benefits, and support for professional development.
Job Type & Location
This is a Permanent position based out of Detroit, MI.
Pay and Benefits
The pay range for this position is $40.00 - $44.00/hr.
Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to specific elections, plan, or program terms. If eligible, the benefits available for this temporary role may include the following:
- Medical, dental & vision
- Critical Illness, Accident, and Hospital
- 401(k) Retirement Plan – Pre-tax and Roth post-tax contributions available
- Life Insurance (Voluntary Life & AD&D for the employee and dependents)
- Short and long-term disability
- Health Spending Account (HSA)
- Transportation benefits
- Employee Assistance Program
- Time Off/Leave (PTO, Vacation or Sick Leave)
This is a fully onsite position in Detroit,MI.
Application Deadline
This position is anticipated to close on Jul 10, 2026.
About Actalent
Actalent is a global leader in engineering and sciences services and talent solutions. We help visionary companies advance their engineering and science initiatives through access to specialized experts who drive scale, innovation and speed to market. With a network of almost 20,000 consultants and 5,000 clients across the U.S., Canada, Asia and Europe, Actalent serves many of the Fortune 500. We are proud to be an Engineering News-Record (ENR) Top 500 Design Firm for our engineering design services and a ClearlyRated Best of Staffing® winner for both client and talent service.
The company is an equal opportunity employer and will consider all applications without regard to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender identity, genetic information or any characteristic protected by law.
If you would like to request a reasonable accommodation, such as the modification or adjustment of the job application process or interviewing process due to a disability, please email [email protected] for other accommodation options.
San Francisco Fair Chance Ordinance: Pursuant to the San Francisco Fair Chance Ordinance, for all positions located in the city and county of San Francisco, we will consider for employment qualified applicants with arrest and conviction records.
Massachusetts Lie Detector: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
Use of Artificial Intelligence (AI): We may use Artificial Intelligence (AI) to support parts of our hiring process, including sourcing, screening, and evaluating candidates. AI helps assess applications and qualifications, but final decisions are made by our hiring team. By applying, you acknowledge and agree that your application may be reviewed using AI tools.
