Job Description
Are you an experienced Data Engineer with a desire to excel? If so, then Talent Software Services may have the job for you! Our client is seeking an experienced Data Engineer to work at their company in Melvindale, MI.
Position Summary : Conducts data integration and analytics projects that automate data collection, transformation, storage, delivery, and reporting processes. Ensures optimization of data retrieval and processing, including performance tuning, delivery design for down-stream analytics, machine learning modelling, feature engineering, and reporting. Works across multiple areas / teams to develop data integration methods that advance enterprise data and reporting capabilities. Ability to work independently and identify appropriate course of action to analyze issues, recommend solutions and administer programs.
Primary Responsibilities / Accountabilities :
- Develops data sets and automated pipelines (Microsoft ADF / ADX) that support data requirements for process improvement and operational efficiency metrics
- Builds reporting and visualizations that utilize data pipeline to provide actionable insights into compliance rates, operational efficiency, and other key business performance metrics
- Ad hoc and project analysis – gathering and reviewing data, making recommendations, and performing follow-through activities (scheduling meetings, modifying data, additional analysis, reporting changes)
- Supporting workload management activities via workforce planning, maintenance, recommendations & tracking through standard processing and systems (Power BI, Power Apps, Power Automate)
- Write / execute queries in databases
- Create visual representations of data sets in quick and understandable means to accurately reflect the dataset
- Gathering requirements to execute reports / projects / analysis
Qualifications :
Minimum : Bachelor’s Degree (Computer Science / Information Systems / Software Engineering, etc,), Microsoft Azure ADF / ADX (ETL processes & KQL)Preferred : Databricks (PySpark, SQL), SQL Server Querying