Analyst - Data Engineering

Location: Louisville - West Market, Louisville - Eastpoint, Louisville - Lily

Remote Type: Hybrid

Time Type: Full time

Job Description

Company:

Marsh

Description:

We are seeking a Data Engineer to join our Applications Development team at Marsh in Louisville, KY. This is a hybrid role that has a requirement of working at least three days a week in the office.

As a Data Engineer at Marsh, you will conceptualize and implement the setup and management of the data platform built Databricks services across different regions.

We will count on you to:

• Collaborate with stakeholders to understand data requirements and translate them into technical specifications

• Design, develop, and implement data pipelines and ETL processes, ensuring thorough unit testing to validate functionality and performance.

• Implement data quality checks and validation processes to ensure the accuracy and integrity of data throughout the pipeline

• Coordinate with cross-functional teams to ensure alignment on project goals, timelines, and deliverables

• Continuously monitor data workflows and pipelines for performance, reliability, and efficiency, implementing improvements as necessary

• Create and maintain comprehensive documentation for data processes, architecture, and workflows to ensure knowledge sharing and compliance

What you need to have:

• Bachelor’s degree in computer science, Data Science, Information Technology, or a related field

• Proficiency in programming languages such as Python and SQL, along with experience in data modeling and database design

• 5+ years of experience working as a Data Engineer and possess a strong understanding of ETL and ELT concepts

• Experience with API integration and Data ingestion from various sources, ensuring seamless data flow between systems

• Experience with data testing (functional and automated) including proper documentation procedures and automation principles

What makes you stand out:

• Familiarity with data processing frameworks, particularly Apache Spark.

• Experience working with cloud platforms such as AWS or Azure

• Experience with AI integration on test environments

• Ability to manage QA Engineers and guide through SCRUM calls

• Familiarity with data warehousing solutions and technologies, including Databricks and Snowflake.

Why join our team:

• We help you be your best through professional development opportunities, interesting work and supportive leaders.

• We foster a vibrant and inclusive culture where you can work with talented colleagues to create new solutions and have impact for colleagues, clients and communities.

• Our scale enables us to provide a range of career opportunities, as well as benefits and rewards to enhance your well-being.

Marsh (NYSE: MRSH) is a global leader in risk, reinsurance and capital, people and investments, and management consulting, advising clients in 130 countries. With annual revenue of over $27 billion and more than 95,000 colleagues, Marsh helps build the confidence to thrive through the power of perspective. For more information, visit marsh.com, or follow us on LinkedIn and X.

Marsh is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age background, disability, ethnic origin, family duties, gender orientation or expression, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, veteran status (including protected veterans), or any other characteristic protected by applicable law. If you have a need that requires accommodation, please let us know by contacting reasonableaccommodations@marsh.com.

Marsh is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one “anchor day” per week on which their full team will be together in person.