The Intersect Group is seeking a Data Engineer II for client located in the Tulsa area. An engineer proficient in integrating diverse data sources and transforming data for various business applications.

Direct Hire

Location: Tulsa / 5 days onsite (relocation assistance available)

Interview Process: 2 virtual interviews followed by onsite interview

Skills:

• Databricks & Databricks SQL
• Python and PySpark Libraries
• T-SQL
• Azure Data Factory
• SSIS
• Azure DevOps Pipelines and Repositories
• Azure Synapse and/or Power BI Modeling is a plus
• Looking for engineers with at least 3 years’ experience

Needed:

• 3-5 years’ experience in programming data solutions.
• Familiar with all aspects of systems analysis, design, and installation procedures in a business environment.
• Proficient in one or more of the company’s data technologies or languages.
• Good problem-solving skills.
• Familiar with a variety of IT concepts, practices and procedures.
• Good written and verbal communication skills and time management skills.

Preferred:

• 5+ years professional experience including developing data solutions in a business environment, installing and troubleshooting hardware and software problems.
• Proficiency in all programming languages and data tools in use at company

This role is part of a team dedicated to developing innovative data solutions using the Azure and Databricks platform. While our data warehouse and Power BI models provide valuable insights for business users, we continuously strive to optimize performance and introduce new capabilities to enhance data-driven decision-making. This engineer is responsible for developing, testing, deploying, supporting, and maintaining data pipelines, data stores (e.g., Data Warehouse, Mart, Hub), and business intelligence models. The position follows established guidelines and instructions to execute job functions effectively.

Duties:

Development - 50%

• Develop, modify, extend, and debug data pipelines in alignment with Software Development Lifecycle (SDLC).
• Data Extraction and Analysis: Connect to diverse data sources, analyze data, and assess its suitability for business needs.
• Automated Data Pipeline Development: Design and implement automated pipelines to extract, cleanse, and transform data for business use.
• Data Consolidation: Build automated processes to integrate and unify similar data from multiple sources into a single source of truth (e.g., store, product, employee data).
• Data Quality Monitoring: Develop automated processes for data quality monitoring and alerting.
• Data Modeling and Publishing: Structure and publish datasets for users to access through reporting and business intelligence tools.
• Technical Expertise: Apply knowledge of multiple programming languages and tools used in development process, including ETL, T-SQL, data profiling, MDM tools, BI modeling tools (e.g., SSAS, Power BI), and programming languages such as C#.

May act as a Product Technical Owner of a software product on occasion:

• Accountable for the technological performance of the product: Software, Hardware, Virtual Ware
• Tech Teams – Development, Data, Infrastructure, Contractors, and Professional Services
• Responsible for adherence to strategic plan while remaining focused on the teams handling the product.
• Responsible for the technical requirements.
• Responsible for Technical User Story acceptance.
• Manages the technical debt of the product.
• Manages conflicts of interest within the development team.
• Coordinates coding efforts across one or more development teams.
• Holds Development, Technical, Professional Services, Data, and other IT teams accountable within the framework of the product.
• Accepts input and guidance from our Architecture, Infrastructure and Development teams and acts as the one voice back to Professional Services on technology related items when decisions need to be made.
• Leads trouble-shooting efforts by getting the right expertise involved and calling “war rooms” together when necessary.
• Acts as Scrum Master when the development team and PTO agree this is appropriate.

Technical Support - 35%

• Troubleshoot and resolve technical issues by applying strong customer service, problem-solving, and analytical skills while adhering to established support processes and metrics.
• Analyze and track incoming issues to identify root causes, develop technical and training solutions to reduce recurrence and impact, and report findings to management.
• Accurately document customer issues, resolution steps, and feedback in support tracking software to identify and address recurring technical problems.
• Create and distribute internal support documentation for troubleshooting, training, and other operational needs.
• Collect and relay customer feedback and improvement suggestions for product enhancements.
• This role requires 24/7 support availability.

Training - 10%

• Seek feedback from team members and supervisors to identify areas for skill improvement.
• Apply received feedback to daily work, continuously striving to enhance performance.
• Train with senior developers to expand development skills and deepen system knowledge.
• Utilize various training resources, including self-study, in-house classes, seminars, and online courses, to enhance technical expertise.
• Stay current with industry best practices, emerging technologies, and professional developments by attending workshops, reviewing publications, and evaluating new solutions for organizational fit.
• Mentor junior data engineers through knowledge sharing, code reviews, and hands-on training to strengthen team capabilities.

Administration and Communication - 5 %

• Actively listen to team members and incorporate their input.
• Communicate ideas effectively in both verbal and written formats.
• Prepare clear, professional, and grammatically accurate business correspondence.
• Provide timely status updates to project managers, team members, key stakeholders, and supervisors regarding assignments and scheduling needs.
• Maintain accurate records of project work and trouble call resolutions within department-defined timeframes.
• Record time tracking.
• Identify individual task progress.
• Identify task completion.