Electrical Components International (ECI) is looking for a Data Engineer to join our team in Southfield, MI. This is an on-site position.

Who We Are

Founded in 1953, Electrical Components International (ECI) is one of the world’s leading suppliers of electrical distribution systems, control box assemblies, and other critical engineered components for diversified markets. With 25,000 employees and 37 global manufacturing locations, ECI is the trusted partner to market leaders with 500+ customers. At ECI, we power smart, connected, and electrified solutions^TM that help solve the most complex challenges.

Since 2020, we have embarked on a successful journey to transform the company, delivering significant value to our customers, investors and employees. As part of our strategic plan, we have defined key pillars to support and accelerate on our growth trajectory. One of these core pillars is focused on driving excellence through enhanced capabilities, tools and processes. To execute our strategy, we are looking to strengthen our organization with a Data Analyst.

Key Responsibilities

We are seeking a highly skilled Data Engineer to design, develop, and maintain our data pipelines and analytics solutions. The ideal candidate will have a strong foundation in SQL, PySpark, and Python, along with hands-on experience in building scalable data pipelines, processing large datasets, and transforming raw data into actionable insights. As a Data Engineer, you will play a crucial role in designing and maintaining the data infrastructure that supports our business intelligence, machine learning, and analytics teams.

In this role, you will:

• Design, develop, and optimize data pipelines using SQL, PySpark, and Python to process large datasets from various data sources.
• Implement and maintain ETL processes to extract, transform, and load data efficiently into data lakes, warehouses, or databases.
• Optimize SQL queries for performance, ensuring efficient data retrieval and processing.
• Utilize PySpark for distributed data processing tasks, handling large-scale datasets across clusters.
• Develop automated data pipelines for continuous integration and delivery (CI/CD) of data-related tasks.

• Build and Optimize Data Pipelines: Design, architect, and maintain efficient data pipelines that seamlessly move data from various sources to consumption endpoints. Oversee the full lifecycle of data—from acquisition and integration to delivering actionable insights for specific business use cases. Ensure that data pipelines are optimized for scalability, reliability, and performance, managing the transition from development to production environments.

• Ensure Data Governance and Compliance: Collaborate with data governance teams to ensure responsible data usage, adhering to organizational policies and legal regulations. Contributes to the creation and maintenance of a curated data catalog that promotes the governed reuse of data for analytics and operational purposes.
• Leverage Big Data and Analytics Technologies: Utilize Azure Databricks, Apache Spark, and other big data tools to manage and analyze large datasets. Design and implement data workflows to support advanced analytics, machine learning models, and other data-driven applications.
• Implement CI/CD Pipelines with Azure DevOps: Develop and manage CI/CD pipelines using Azure DevOps to automate the deployment, testing, and continuous integration of data pipelines and analytics workflows. Ensure efficient deployment with minimal downtime and maximum accuracy.
• Other duties as assigned.

Education & Experience

• Bachelor’s degree in Computer Science or Information Systems, preferred, or equivalent work experience.
• 3 -5 years of experience in data management disciplines, including data warehousing, integration, modeling, optimization, data quality, or related areas with direct relevance to data engineering responsibilities on the Microsoft Azure Platform.
• Experience with implementation and support of Azure cloud services, including but not limited to: Azure Data Factory, Azure Data Lake Store, Azure Data Lake Analytics, Azure Analysis Services, Azure SQL, Azure DW, Azure Analytics Services, and Synapse Analytics.
• Hands-on experience with developing both multidimensional and tabular models for large, complex datasets.
• Proven experience as a Data Engineer with expertise in SQL, PySpark, and Python.
• Strong understanding of relational databases (e.g., SQL Server, MySQL, PostgreSQL) and data warehousing concepts.
• Experience with distributed computing frameworks such as Apache Spark and PySpark for big data processing.
• Proven proficiency in SQL and Python scripting for data manipulation and automation.
• Expertise with Azure Synapse Analytics and Azure SQL Server Hyperscale for data warehousing, large-scale data processing and analytics.

Knowledge, Skills & Abilities

• Drive Automation through Metadata Management: Spearhead automation efforts for repetitive, manual data preparation and integration tasks, leveraging modern tools, techniques, and architectures. The focus is on minimizing errors, improving productivity, and enhancing the efficiency of data workflows.
• Collaborate Across Departments: Work closely with cross-functional teams, including business analysts, to refine data requirements for analytics initiatives. Facilitate communication across departments to ensure the availability and actionable nature of the right data for diverse stakeholders.
• Educate and Train Stakeholders: Stay current with evolving data management trends and emerging technologies to meet new data requirements. Train and guide both team members and business users in efficient data pipelining, integration, and preparation techniques. Foster a culture of knowledge-sharing, continuous learning, and process improvement across the organization.
• Strong interpersonal and communication skills, with the ability to interface effectively with stakeholders at all levels within the company.
• A confident, energetic self-starter with a strong sense of urgency, excellent judgment, and a demonstrated commitment to high standards of ethics, regulatory compliance, customer service, and business integrity.

Company Values & Job Competencies

• Company Values: Safety, Accountability, Integrity & Ethics, Respect & Empathy
• Core Competencies: Communication, Teamwork & Collaboration, Flexibility & Adaptability
• Individual Contributor Job Competencies: Quantity & Quality of Work, Technical Skills & Continuous Learning
• Supervisor & Manager Job Competencies: Decision Making, Developing Others, Continuous Improvement
• Director & Above Job Competencies: Leadership, Strategic Thinking, Results

Primary Location

The Data Engineer will be based on-site in Southfield, Michigan.

Our Culture

At ECI, we live by our core values of respect, empathy, accountability, integrity, and ethics. Our diverse, equitable, and inclusive culture empowers our people to be who they are, contribute their unique perspectives, and make a difference individually and collectively. It enables us to leverage different perspectives and encourage new ideas.

Our commitment to operational and commercial excellence begins with our commitment to ethical excellence. We deliver results as One Team and follow through on our promises.

Physical Demands & Work Environment

• Must be able to remain in a stationary position 50% of the time.
• Needs to occasionally move about inside the office to access file cabinets, office machinery, etc.
• Ability to communicate information and ideas clearly and accurately.
• Constantly operates a computer and other office productivity machinery.
• Ability to observe details at close range.
• Frequent hearing on the phone and in person.
• Constant reading.
• Constantly positions self to maintain files in file cabinets.
• Occasional travel to other work sites.
• Works in general office conditions.

Electrical Components International is an Equal Employment Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.

Federal Applicant Information Poster

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