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.
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