Salesforce Developer

Experimental Design Software Versioning Feature Engineering Test Data Generation Operational Databases Cloud-Native Computing NumPy (Python Package) Distributed Data Store Continuous Development New Product Development Artificial Intelligence Pandas (Python Package) SQL (Programming Language) Engineering Design Process Automated Machine Learning Snowflake (Data Warehouse) Extract Transform Load (ETL) Python (Programming Language) Scikit-Learn (Python Package) MLOps (Machine Learning Operations) Tableau (Business Intelligence Software) Machine Learning Model Monitoring And Evaluation, 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., * Design, develop, and maintain scalable data pipelines using Databricks, PySpark, and cloud-native tools to ingest, clean, and transform large time series datasets.

• Explore, evaluate, and implement new tools and techniques to improve data processing, modeling, and automation across the data lifecycle.
• Design and maintain data models optimized for analytical and machine learning workloads, with a particular focus on time series data.
• Build, train, and evaluate machine learning models for forecasting, anomaly detection, and pattern recognition in time series datasets.
• Create analysis modules for vehicle test data and ensure they meet the needs of automotive product development or manufacturing use cases.
• Collaborate closely with cross-functional engineering and product teams to understand data needs, define requirements, and deliver high-quality analytical solutions.
• Constantly communicate with engineering teams to understand mechanics, electrical, and controls problems and translate them into data-driven analyses.
• Optimize Spark and other distributed data processing jobs for performance, reliability, and cost efficiency.
• Implement and uphold best practices for data quality, including validation, monitoring, and data governance.
• Establish and maintain robust versioning, testing, and documentation practices for data pipelines, models, and analytics assets.
• Build and maintain ETL/ELT pipelines in cloud environments to support both batch and potentially streaming data workloads.
• Apply machine learning fundamentals to real-world datasets and integrate models into production data pipelines.
• Translate complex technical and analytical findings into clear, actionable business insights for technical and non-technical stakeholders.
• Contribute to shaping the overall data strategy and architecture for high-impact analytical products and solutions., 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. Related Jobs Data Engineer Actalent Detroit, MI*On-Site NoSQL CI/CD MLflow Tooling PySpark Power BI Big Data Mechanics Visionary Pipelines Automation Innovation Statistics Databricks Scalability Reliability Forecasting AWS Kinesis Time Series Data Quality Data Science Communication Data Modeling Collaboration Data Strategy Data Pipelines Microsoft Azure Data Processing Amazon Redshift Causal Inference Machine Learning Data Engineering Anomaly Detection Data Visualization Amazon Web Services Pattern Recognition Experimental Design Software Versioning Feature Engineering Test Data Generation Operational Databases Cloud-Native Computing NumPy (Python Package) Distributed Data Store Continuous Development New Product Development Artificial Intelligence Pandas (Python Package) SQL (Programming Language) Engineering Design Process Automated Machine Learning Snowflake (Data Warehouse) Extract Transform Load (ETL) Python (Programming Language) Scikit-Learn (Python Package) MLOps (Machine Learning Operations) Tableau (Business Intelligence Software) Machine Learning Model Monitoring And Evaluation +0

Tooling PySpark Power BI Big Data Mechanics Visionary Pipelines Automation Innovation Statistics Databricks Scalability Reliability Forecasting AWS Kinesis Time Series Data Quality Data Science Communication Data Modeling Collaboration Data Strategy Data Pipelines Microsoft Azure Data Processing Amazon Redshift Causal Inference Machine Learning Data Engineering Anomaly Detection Data Visualization, * 3+ years of experience in data engineering, data science, or a hybrid data engineering/data science role.

• Strong proficiency with Databricks or comparable big data platforms (such as Snowflake, Amazon Redshift, or other Spark-based or cloud-native analytics frameworks).
• Hands-on experience with PySpark and distributed data processing for large-scale datasets.
• Experience building and maintaining ETL/ELT pipelines in a cloud environment such as Azure, AWS, or GCP.
• Hands-on experience working with time series data, including feature engineering, forecasting, and anomaly detection.
• Strong programming skills in Python with professional experience, including 1-5 years working with Python in an automotive environment.
• Familiarity with common data science libraries such as pandas, NumPy, and scikit-learn.
• Experience with MLflow, Delta Lake, or Databricks AutoML for managing experiments, models, and data.
• Strong SQL skills and experience working with large relational or NoSQL databases.
• Understanding of machine learning fundamentals and experience applying models to real-world datasets.
• Ability to translate complex technical concepts and analytical results into clear business insights.
• Strong communication and collaboration skills to work effectively with cross-functional teams.
• Curiosity, an ownership mindset, and a willingness to explore new tools, techniques, and approaches.
• Comfort working in a fast-paced, iterative environment with evolving requirements.

Additional Skills & Qualifications

• Experience in an automotive product development or manufacturing environment, particularly working with vehicle test data.
• Experience creating analysis modules for vehicle test data and supporting engineering teams focused on mechanics, electrical, and controls.
• Familiarity with streaming data technologies such as Structured Streaming, Kinesis, or similar frameworks.
• Background in MLOps, including CI/CD for data pipelines and productionizing machine learning models.
• Experience with data visualization tools such as Power BI, Tableau, or similar platforms.
• Knowledge of statistics, experimental design, or causal inference to support robust analytical conclusions.
• Experience implementing new tools and techniques to enhance data processing, modeling, and automation.
• Exposure to cloud-native analytics frameworks and modern data architectures using tools like Delta Lake and AutoML.
• Interest in shaping data strategy and architecture for high-impact analytical products.
• Motivation to work in a collaborative team environment that values experimentation, learning, and technical excellence.

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) Workplace Type

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.