Junior Data Engineer

TEKsystems•Kansas City, KS

7d•$39 - $43•Hybrid

About The Position

Seeking a Junior Data Engineer to join the Data Architecture, Engineering and Analytics team. This role will support enterprise data engineering initiatives focused on migrating legacy data warehouse solutions into Databricks and Azure. The engineer will work with data architects and data engineers to build and maintain data pipelines, support data delivery projects, and contribute to the organization's modernization efforts. The ideal candidate will possess Databricks, Python, and Azure experience, strong communication and collaboration skills, and a desire to grow within a high-performing data organization. The individual will participate in multiple data engineering projects, support enterprise data-sharing initiatives, and assist with the transition from legacy DB2-based systems to a modern cloud data platform.

Requirements

1-3 years of data engineering or related experience (Associate Analyst level).
Basic understanding of data modelling, mapping and data quality/governance practices.
Bachelors degree in software engineering, computer science, computer information systems, or related degree, or equivalent professional experience.
Must be able to read/write SQL in the following environments (SQL Server, Oracle, DB2).
Experience working in cloud data environments (AWS, Azure).
Experience working with AWS or Azure workflow orchestration tools.
Experience working with one or more columnar storage systems (Snowflake, Redshift, BigQuery, etc.).
Must have completed at least one full cycle of building a data lake and/or a data warehouse.
Knowledge and skills with Power BI will be important, not critical.
Strong business communications skills for requirements gathering and development.
Ability to multi-task and change priorities.

Nice To Haves

Worked with or built Data Lakes, Data Warehouse in a hybrid environment (cloud / on-premises).
Experience working with CRM systems like Salesforce.
Experience with end-to-end supply chain or merchandising.
Exposure to data streaming tools and technologies like Kafka, TensorFlow or similar.
Basic knowledge and understanding of statistics and awareness of data science methodologies.

Responsibilities

Troubleshoot and develop solutions to problems, including using AWG approved AI tools such as Gemini, CoPilot and NotebookLM.
Collaborate with other developers and support engineers to resolve production, enhancement or development issues.
Participate in an on-call rotation for integration and transformation pipelines, legacy systems, and modern data platforms that may involve occasional off-hours and weekend support.
Take ownership of following on-call procedures and instituting permanent fixes for repetitive problems.
Maintain documentation for legacy systems, jobs, modern pipelines, and modernization implementation.
Understand and implement change control procedures (including RFC, CAB, CI/CD).
Build real-time and batch data integrations from disparate source systems into the data lake/data warehouse/delta lake.
Build and maintain scalable ETL processes using workflow automation tools.
Provide documentation (including Technical Design Documents) for installations and deliverables.
Design dimensional models and be able to cleanse and transform raw data into structured formats.
Administer and maintain data pipelines used for loading data into the data warehouse or lakehouse.
Scale and tune data pipelines, data sets, and SQL queries.
Responsible for Unit testing, support of Integration testing, and User Acceptance Testing.
Develops timely and proper change documentation.
Proactively communicates status to key stakeholders to diagnose and ensure delivery is on track.
Takes ownership of assignments.
Proactively drives results and seeks support when hitting barriers.
Exhibits curiosity to understand how changes fit into the overall scope.
Responsible for understanding and adoption of IT Architecture practice.
Continuous learning of existing and future data technologies and tools.
Apply standard methodologies to analyze, design, develop, test, and deploy data management solutions.
Participate in agile story authoring, sizing, and demo sessions for developed features.
Participate in code reviews and receive feedback from the team.
Propose process improvements for continuous department maturity.
Collaborate with business partners to understand their business problems or needs and desired outcomes.
In collaboration with other members of the team and user community, configure cloud-based capabilities that enable the AWG community.
Communicate priorities to the technology organization to drive effective business solutions.
Maintain verbal and written issue identification and status updates to cross-functional teams and leadership.