7-12 years of experience in data engineering or analytics
Proficient in SQL and working knowledge of Python
Hands-on experience with modern data tools such as Azure Data Factory or Snowflake
Familiarity with cloud environments like AWS or Azure
Understanding of data integration and quality principles
Strong problem-solving and communication skills
Bachelor's degree in Computer Science or a related field
Responsibilities
Build and maintain scalable data pipelines
Develop ETL/ELT processes for data transformation
Collaborate to gather requirements and ensure data quality
Assist in optimizing cloud-based data models
Support the creation of dashboards and visualizations
Participate in testing and deployment of data solutions
Engage in project workstreams for client interaction
Benefits
Supportive environment emphasizing mentorship and professional growth
Opportunity to work with experienced architects and consultants
Exposure to various industries and data challenges
Collaborative team focused on solving complex business problems
Chance to develop technical and consulting skills in a client-facing role
Full Job Description
Managing Consultant, Data Engineer
Department: Data Analytics
Employment Type: Full Time
Location: Atlanta
The RoleWe are looking for a technically skilled and motivated Data Engineer with 7-12 years of experience to join our growing Data & Analytics team based in Atlanta, GA. In this role, you'll work closely with cross-functional teams to build modern data pipelines, develop scalable solutions, and help clients unlock insights from their data. You'll be supported by experienced architects and consultants while having the opportunity to grow your technical and consulting skills in a collaborative, client-facing environment. What You'll Do
Build and maintain scalable, reliable data pipelines using tools like Azure Data Factory, AWS Glue, or Palantir Foundry
Develop ETL/ELT processes to transform and prepare raw data for reporting, analytics, and downstream applications
Collaborate with team members and clients to gather requirements, integrate data sources, and ensure high data quality
Assist in the development and optimization of data models and cloud-based data platforms (e.g., Snowflake, Databricks, Redshift)
Support the creation of dashboards and data visualizations using tools like Power BI or Tableau
Participate in testing, documentation, and deployment of data solutions to ensure performance and reliability
Engage in project workstreams alongside more senior team members, gaining exposure to client interaction and delivery best practices
Learn and apply modern data engineering and cloud practices in a variety of industries and use cases
Who You'll Work With
A team of collaborative, experienced consultants focused on solving complex business problems through data
Clients across industries who are looking to modernize their data platforms and make more informed decisions
Colleagues who prioritize curiosity, humility, and hands-on problem-solving A supportive environment where ongoing learning and mentorship are central to your professional growth
What You'll Bring
7-12 years of professional experience in data engineering, analytics, or a related technical role
Proficiency in SQL and working knowledge of Python or another scripting language
Hands-on experience with ETL/ELT processes and modern data tools such as Azure Data Factory, AWS Glue, Snowflake, or Databricks
Familiarity with cloud environments (AWS, Azure, Palantir Foundry or similar) and data modeling concepts
Understanding of data integration, quality, and performance tuning principles
Ability to work collaboratively on fast-paced projects with a mix of technical and non-technical stakeholders
Strong problem-solving and communication skills
Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field
Currently reside in Atlanta, GA or willingness to relocate at your expense.
Ability to legally work for any employer in the US without sponsorship
Bonus Points if You Have
Experience with tools like Apache Airflow, dbt, or Palantir Foundry
Familiarity with big data technologies such as Spark, Kafka, or Redshift
Exposure to dashboarding and visualization tools like Power BI or Tableau
Certifications in cloud platforms or data engineeringtechnologies
