Key Responsibilities:
- Governance & Compliance: Support data, compliance, and environment governance processes for the assigned domain. Facilitate an intake process to reduce rework and promote reuse of analytics solutions.
- Data Integration & Cleansing: Collaborate with peers to integrate data from warehouses, data lakes, and other source systems. Cleanse data to ensure report accuracy and reduce duplication, maintaining documentation of the cleansing process.
- Analytics Projects: Support analytics projects to produce insights for business decision-making. Deliver results using reports, business intelligence technology, or other appropriate mechanisms.
- Standards & Guidelines: Support the business in establishing and enforcing guidelines and standards for data collection, integration, and processes.
- Data Ingestion: Support project work to ingest key data into the data lake, ensuring the creation and maintenance of relevant metadata and data profiles.
- Stakeholder Assistance: Assist stakeholders and business teams with finding necessary and relevant data. Participate in communities of practice promoting the responsible use of analytics.
- Training & Communication: Coach and assist business users in developing capabilities to conduct work in the analytics ecosystem. Assist with the preparation of communications to leaders and stakeholders.
Data Analytics & Visualization:
- Design, develop, and maintain interactive dashboards and reports using Power BI to provide actionable insights.
- Create and optimize data models to support visualization and analytics needs.
- Implement statistical models and techniques to analyze business data and derive meaningful insights.
ETL & Data Management:
- Design and develop ETL pipelines to extract, transform, and load data from various sources.
- Ensure data accuracy, integrity, and consistency across different platforms.
- Work with relational databases, writing and optimizing SQL queries for data processing.
Application Development & Automation:
- Develop applications and process automation using Power Apps to streamline business processes.
- Integrate Power Apps with Power BI, SharePoint, and other enterprise systems.
Team Leadership & Project Management:
- Lead a team of data analysts and data engineers, providing technical guidance and support.
- Manage project timelines and deliverables, ensuring the successful execution of data-driven initiatives.
Advanced Analytics & Platform Expertise:
- Leverage Databricks and PySpark to perform advanced analytics, build scalable data pipelines, and optimize data workflows.
- Utilize statistical and machine learning models to solve complex business problems.
- Explore and implement solutions using low-code/no-code platforms such as Mendix (preferred).
Experience: 6-8 years of relevant work experience required. Experience in manufacturing analytics or a related domain is preferred.
Skills:
- Technical Skills:
- Strong knowledge of statistics and experience with statistical models.
- Hands-on expertise in Power BI, Power Apps, and SQL.
- Knowledge or experience in Mendix platforms is a plus.
- Experience in designing and maintaining ETL processes.
- Knowledge in Databricks and PySpark for data analytics and processing.
- Soft Skills:
- Strong problem-solving and analytical abilities.
- Excellent communication and stakeholder management skills.
- Proven ability to lead a team.
Qualifications:
- Bachelor s degree in Computer Science, Information Technology, or a related field.
Competencies:
- Collaborates: Building partnerships and working collaboratively with others to meet shared objectives.
- Communicates Effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences.
- Customer Focus: Building strong customer relationships and delivering customer-centric solutions.
- Interpersonal Savvy: Relating openly and comfortably with diverse groups of people.
- Data Analytics: Discovering, interpreting, and communicating qualitative and quantitative data to enable data-driven business decisions.
- Data Mining: Extracting insights from data by identifying relationships and patterns.
- Data Modeling: Creating, writing, and testing data models to meet business, technical, security, governance, and compliance requirements.
- Data Communication and Visualization: Constructing a narrative of the business problem, root cause, solution options, and opportunities through data visualization.
- Data Literacy: Expressing data in context, including data sources and constructs, analytical methods, and applied techniques.
- Data Profiling: Assessing data issues and cleansing requirements to ensure quality data.
- Data Quality: Identifying, understanding, and correcting flaws in data to support effective information governance.
- Values Differences: Recognizing the value that different perspectives and cultures bring to an organization.
Role: Database Analyst
Industry Type: Automobile
Department: Engineering - Software & QA
Employment Type: Full Time, Permanent
Role Category: DBA / Data warehousing
