Data Engineering - Associate
About The Position
Build reliable data foundations that help clients turn complex data into trusted, actionable insights. We are seeking a highly motivated Data Engineering Consulting Associate to join our Data & Analytics practice. In this role, you will help clients design, build, and optimize modern data platforms that enable advanced analytics, reporting, and AI-driven decision-making. You will work alongside experienced consultants, solution architects, and client stakeholders to deliver end-to-end data engineering solutions across cloud and on-premises environments. This position offers an excellent opportunity to develop both technical expertise and consulting skills while working on large-scale digital transformation initiatives.
Requirements
- Bachelor's degree in Computer Science, Information Systems, Data Engineering, Engineering, Mathematics, or a related field.
- 1-3 years of experience in data engineering, data integration, analytics engineering, software engineering, or a related technical role.
- Hands-on experience with SQL, relational databases, and ETL/ELT development.
- Understanding of data warehousing concepts, dimensional modeling, and data quality practices.
- Experience with at least one programming language such as Python, Scala, or Java.
- Familiarity with at least one cloud platform such as Microsoft Azure, AWS, or Google Cloud.
- Strong analytical, problem-solving, communication, and documentation skills.
- Ability to work collaboratively in a team-oriented, client-facing environment.
Nice To Haves
- Experience with Azure Data Factory, Microsoft Fabric, Databricks, Synapse Analytics, Snowflake, Redshift, BigQuery, Airflow, dbt, or comparable platforms.
- Knowledge of distributed data processing frameworks such as Apache Spark.
- Exposure to data governance, metadata management, master data management, or data observability.
- Experience in consulting, professional services, or another client-facing delivery environment.
- Relevant certifications from Microsoft Azure, AWS, Google Cloud, Databricks, or Snowflake.
Responsibilities
- Design, develop, test, and maintain scalable data pipelines and ETL/ELT processes.
- Support the implementation of modern data platforms, data lakes, and data warehouses.
- Develop data integration solutions using cloud-native and enterprise technologies.
- Build and optimize data ingestion frameworks for structured and unstructured data.
- Perform data quality validation, transformation, reconciliation, and performance tuning.
- Support migration of legacy data environments to modern cloud architectures.
- Gather business and technical requirements from client stakeholders.
- Translate business needs into practical technical data solutions.
- Participate in workshops, design sessions, demonstrations, and project status meetings.
- Document technical designs, architecture decisions, operating procedures, and development standards.
- Support disciplined project delivery across one or more client workstreams.
- Collaborate with business intelligence, analytics, AI, and data science teams to ensure reliable data availability.
- Support the development of curated data models for reporting and analytical use cases.
- Assist with implementing data governance, security, privacy, and compliance controls.
- Identify opportunities to improve platform performance, scalability, reliability, and maintainability.
- Stay current on emerging cloud, data engineering, analytics, and AI technologies.
- Contribute to internal accelerators, reusable assets, proposals, and knowledge-sharing initiatives.
Benefits
- medical
- dental
- vision
- 401(k)
- paid time off
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
