Electrical Engineer jobs in Detroit, MI

Description

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

Qualified candidates must have:

• Bachelor’s degree in computer science, Information Systems, or equivalent work experience; MBA preferred.
• 3 years of experience in data management disciplines including data warehousing, data integration, modeling, optimization, and data quality, and/or other areas directly relevant to data engineering responsibilities and tasks in 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 (Required)
• Experience developing both multidimensional and tabular models with large and complex datasets.

About Us: 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.

About the Position:

The Data Engineer provides strategic, analytical, and technical support to the enterprise data management team. The Data Engineer leverages advanced knowledge on database technologies, operating systems, best practices, and industry trends including database design, configuration, tuning, and support.

Duties Include:

• Build data pipelines: Managed data pipelines consist of a series of stages through which data flows (for example, from data sources or endpoints of acquisition to integration to consumption for specific use cases). These data pipelines must be created, maintained, and optimized as workloads move from development to production for specific use cases. Architecting, creating, and maintaining data pipelines will be the primary responsibility of the data engineer.
• Drive Automation through effective metadata management: The Data Engineer will be responsible for using innovative and modern tools, techniques, and architectures to partially or completely automate the most-common, repeatable and tedious data preparation and integration tasks to minimize manual and error-prone processes and improve productivity. The Data Engineer will also need to assist with renovating the data management infrastructure to drive automation in data integration and management. This will include (but not be limited to):
  • Learning and using modern data preparation, integration and AI-enabled metadata management tools and techniques.
  • Tracking data consumption patterns.
  • Performing intelligent sampling and caching.
  • Monitoring schema changes.
  • Recommending/automating existing and future integration flows.
• Collaborate across departments: The newly hired Data Engineer will need strong collaboration skills to work with varied stakeholders within the organization. Work in close relationship with business (data) analysts in refining their data requirements for various data and analytics initiatives and their data consumption requirements.
• Educate and train: Data Engineer should be curious and knowledgeable about new data initiatives and how to address them. This includes applying their data and/or domain understanding in addressing new data requirements. This person will also be responsible for supporting data ingestion, preparation, integration, and operationalization techniques in optimally addressing these data requirements. The data engineer will be required to train counterparts in these data pipelining and preparation techniques, which make it easier for them to integrate and consume the data they need for their own use cases.
• Participate in ensuring compliance and governance during data use: It will be the responsibility of the Data Engineer to ensure that the data users and consumers use the data provisioned to them responsibly through data governance and compliance initiatives. Data engineer should work with data governance teams (and information stewards within these teams) and participate in vetting and promoting content created in the business and by data scientists to the curated data catalog for governed reuse.

Big Data and Analytics: To handle and analyze enormous volumes of data, Data Engineer should have experience use big data technologies like Azure Databricks and Apache Spark to create data processing workflows and pipelines, to support data analytics, machine

Qualifications

Qualifications:

• Bachelor’s Degree in Computer Science, Information Systems, or equivalent work experience; MBA preferred.
• 3 years of experience in data management disciplines including data warehousing, data integration, modeling, optimization, and data quality, and/or other areas directly relevant to data engineering responsibilities and tasks in 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 (Required)
• Experience developing both multidimensional and tabular models with large and complex datasets.
• 2 years of experience working in cross-functional teams and collaborating with business stakeholders in support of departmental and/or multi-departmental data management and analytics initiatives.
• Foundational knowledge of Data Management practices.
  • Strong experience with various Data Management architectures like Data Warehouse, Data Lake, Data Hub and the supporting processes like Data Integration, Governance, Metadata Management.
  • Strong ability to design, build and manage data pipelines for data structures encompassing data transformation, data models, schemas, metadata and workload management.
  • Strong experience in working with large, heterogeneous datasets in building and optimizing data pipelines, pipeline architectures and integrated datasets using traditional data integration technologies. These should include ETL/ELT, data replication/CDC, message-oriented data movement, API design and access and upcoming data ingestion and integration technologies such as stream data integration and data virtualization.
  • Basic experience in working with data governance/data quality and data security teams and specifically information stewards and privacy and security officers in moving data pipelines into production with appropriate data quality, governance and security standards and certification. Ability to build quick prototypes and to translate prototypes into data products and services in a diverse ecosystem –
• Demonstrated success in working with large, heterogeneous datasets to extract business value using popular data preparation tools to reduce or even automate parts of the tedious data preparation tasks.
• Strong experience with popular database programming languages including SQL, PL/SQL, others for relational databases.
• Exposure to tools like Tools: Microsoft SQL Server Management Studio, SQL Server Analysis Services, SQL Server Integration Services
• Strong Experience in use of big data technologies like Azure Databricks and Apache Spark
• Strong experience with advanced analytics tools for Object-oriented/object function scripting using languages such as R, Python and others.
• Strong experience in working with both open-source and commercial message queuing technologies such as Kafka, Azure Service Bus.
• Ability to automate pipeline development –
  • Strong experience in working with DevOps capabilities like version control, automated builds, testing and release management capabilities using tools like Git.
• Ability to collaborate with technical and business personas –
  • Demonstrated success in working with both IT and business while integrating analytics and data science output into business processes and workflows.
  • Experience working with popular data discovery, analytics, and BI software tools like Tableau, Qlik, PowerBI and others for semantic-layer-based data discovery.
  • Adept in agile methodologies and capable of applying DevOps and increasingly DataOps principles to data pipelines to improve the communication, integration, reuse, and automation of data flows between data managers and consumers across an organization.
• Strong experience supporting and working with cross-functional teams in a dynamic business environment.
  • Required to be highly creative and collaborative. An ideal candidate would be expected to collaborate with both the business and IT teams to define the business problem, refine the requirements, and design and develop data deliverables accordingly. The successful candidate will also be required to have regular discussions with data consumers on optimally refining the data pipelines developed in nonproduction environments and deploying them in production.
• Required to have accessibility and ability to interface with, and gain the respect of, stakeholders at all levels and roles within the company. Is a confident, energetic self-starter, with strong interpersonal skills. Has good judgment, a sense of urgency and has demonstrated commitment to high standards of ethics, regulatory compliance, customer service and business integrity.

Why Should You Apply?

• Excellent benefits, including medical, dental, vision, 401k match, paid time off and 12 holidays.
• Fast-paced and detail-oriented environment where you can have a direct impact on outcomes.
• Workplace flexibility

Compensation:

The salary will be determined based on the candidate's knowledge, skills, and abilities.

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.

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