Cloud Data Engineer

NTT DATA Services•Nashville, TN

1d•$104,240 - $156,360•Onsite

About The Position

NTT DATA is seeking a skilled Data Engineer to join our Data Village team. This role involves working on-site in Nashville or Plano as part of a dynamic team focused on delivering cutting-edge data solutions. The ideal candidate will have at least 5 years of experience in data engineering, with expertise in Databricks, Snowflake and AWS data services.

Requirements

At least 5 years of experience in data engineering.
Proficiency in Snowflake and Cloud data services.
5+ years of experience working with cloud services.
2+ years of experience working with Databricks or Snowflake.
3+ years working with PySpark.
Strong knowledge of data warehousing concepts.
Advanced skills in Python or Java programming for data engineering and data pipelines.
Proficiency in integrating data from various sources.
Strong knowledge of data modeling, storage and design within Snowflake.
Experience in securing data based on role and policy definitions.
Experience in building and managing data pipelines.
Experience AWS, Azure, or GCP data services.
Proficiency in using GitHub for version control.
Ability to quickly learn new technologies by applying current skills.
Operate within a sprint model. Stories are assigned, developed, validated, and peer reviewed.
Each story typically involves: Writing and executing scripts. Validating results and capturing observations Documenting outcomes in Confluence Conducting peer reviews and merging code into Git branches
Present deliverables and findings to the architecture team for feedback and alignment.
Ability to adapt to new technologies quickly and efficiently.

Nice To Haves

Apache Iceberg file format
Databricks
Dremio
Spark
Financial data analysis, risk, and compliance data management.

Responsibilities

Utilize your ETL/Data Engineering expertise in Databricks, Snowflake and Cloud data services to build and maintain robust data solutions.
Lead the evaluation of various catalogs and query engines for the Data Lakehouse platform, documenting findings and reviewing them with the architecture teams.
Build and manage dozens of data pipelines to source and transform data based on business requirements.
Apply your knowledge in financial data analysis, risk, and compliance data management to support our financial services customers.
Leverage Databricks and Snowflake for data analysis and discovery, ensuring data is accessible and actionable.
Leverage 10+ sources of data to derive insights.
Quickly learn new technologies by applying your current skills, staying ahead of industry trends and advancements.
Self-identify the need for new skills to be developed and adopt new technologies into your skill set in a month’s time.
Work closely with financial services clients to build modern data solutions that transform how they leverage data for key business decisions, investment portfolio performance analysis, and risk and compliance management.
Manage multiple stakeholder groups and their requirements.
Collaborate within a Pod of 4+ data engineers, working towards common objectives in a consultative fashion with clients.
Use Cloud native ETL services (i.e., AWS Glue or Snaplogic) and Python/SQL for data movement, streaming, and transformation services, ensuring efficient and reliable data workflows.
Work with a client that is leading the industry in using data to drive business decision optimization and investment management strategies.