Working Student contributing to data engineering projects for AI/ML workflows while gaining hands - on experience with data pipelines and tools.
About the role
- Senior Data Engineer at Kroll responsible for designing and maintaining data pipelines. Collaborating across teams to enhance analytics and governance at scale.
Responsibilities
- Build, maintain, and optimize data pipelines and ETL/ELT processes to support enterprise data products and analytics.
- Integrate data from diverse systems, ensuring consistency, quality, and traceability.
- Partner with engineers and architects to enhance the firm’s Azure-based data platform, including Data Factory, Synapse, and Data Lake.
- Implement data transformation and validation logic for improved performance and accuracy.
- Translate business requirements into data models, metrics, and visualizations that drive decision-making.
- Develop dashboards and reports in Power BI or Tableau that communicate insights effectively to stakeholders.
- Use SQL and Python to perform ad hoc analyses, identify patterns, and quantify business performance.
- Support the definition and monitoring of enterprise KPIs and data quality metrics.
- Collaborate with the CDO’s data governance and stewardship teams to ensure data is well-documented, accurate, and compliant with standards.
- Maintain metadata and lineage documentation to support enterprise data catalog initiatives.
- Contribute to the continuous improvement of data quality, integrity, and accessibility across the organization.
- Work closely with business, engineering, and data science teams to operationalize analytical solutions.
- Act as a bridge between technical and business domains, ensuring requirements are clearly understood and delivered.
- Operate within an agile environment, managing priorities independently and delivering high-quality results on time.
Requirements
- Proven experience of 4-7 years in data analytics or data engineering roles with end-to-end data pipeline exposure.
- Strong proficiency in SQL, data modeling, and relational/non-relational database design.
- Experience with ETL tools and data orchestration frameworks (e.g., Azure Data Factory, Databricks, Airflow).
- Proficiency in Python and libraries such as Pandas or NumPy.
- Experience building dashboards and visualizations in Power BI or Tableau.
- Familiarity with data governance, metadata management, and data cataloging principles.
- Excellent analytical problem-solving and communication skills.
- Comfortable working independently while collaborating across teams and time zones.
Benefits
- Health insurance
- Retirement plans
- Paid time off
- Flexible working arrangements
- Professional development
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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