5 months ago
London, United KingdomMid Level / Senior

Responsibilities

  • Build and maintain ETL processes that integrate data from multiple sources into the data lakehouse.
  • Support AWS cloud infrastructure using services including S3, Glue, Lambda, Step Functions, Lake Formation, CloudWatch, and IAM.
  • Develop and maintain Power BI dashboards and reports for stakeholders.
  • Monitor data quality and validate the accuracy, completeness, and reliability of data products using dbt.
  • Write complex SQL queries for data extraction, manipulation, and transformation.
  • Use Python for data processing, scripting, manipulation, analysis, and automation.
  • Use Git for version control and collaborative codebase management.
  • Work with data analysts, data scientists, and cross-functional teams to understand requirements and deliver solutions.
  • Create and maintain technical documentation for data workflows, processes, and systems.

Requirements

  • Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field.
  • 3–5 years of experience in data engineering or a related field.
  • Proficiency in SQL for data manipulation and querying.
  • Experience with Power BI for data visualization and dashboard creation.
  • Experience with Python for data processing and scripting.
  • Familiarity with AWS services including S3, Glue, Lambda, Step Functions, Lake Formation, CloudWatch, and IAM.
  • Strong problem-solving, attention to detail, communication, interpersonal, teamwork, and independent-working skills.
  • Preferred experience with data warehousing concepts and technologies.
  • Preferred knowledge of Tableau, Looker, and data modelling techniques.
  • Preferred familiarity with Hadoop, Spark, Data Mesh, Fabric, Terraform, CI/CD pipelines, Dremio, and Databricks.

Benefits

  • Professional development opportunities, interesting work, and supportive leaders.
  • Inclusive and flexible work environment with opportunities to create solutions and have impact.
  • Career opportunities, benefits, and rewards intended to enhance employee well-being.
  • Hybrid work arrangement with at least three days per week in the local office or onsite with clients; office-based teams will have at least one weekly anchor day.

Tech Stack

Apache HadoopApache SparkAWSDatabricksdbtGitPythonSQLTerraform

Categories

Data Engineering
Marsh & McLennan Companies

About Marsh & McLennan Companies

501-1,000 employees

Marsh McLennan is a global professional services firm providing risk, insurance and reinsurance brokerage, health, wealth, and management consulting to corporations, governments, and nonprofits. It operates through Marsh, Guy Carpenter, Mercer, and Oliver Wyman, earning fees and commissions for advisory, analytics, and placement services. Founded in 1905 and headquartered in New York, it is publicly traded on the NYSE under the ticker MMC.

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