Sr. Data Engineer

Job Description Job Overview

Insight Global is looking for a Senior Data Engineer to join the Data Analytics team at one of our logistics company clients. This person will collaborate closely with multiple stakeholders across the enterprise and Information Technology (IT) group to ensure the most important data is accessible and well‑understood.

The Senior Data Engineer designs, develops, implements, and supports new and existing highly efficient ELT/ETL processes and data sets. Other responsibilities include working closely with data consumers, solution architects, security and governance teams to implement solutions to answer complex questions and drive business decisions. Apply your proven communication skills, problem‑solving skills, and knowledge of best practices in designing, developing, and deploying data and analytic solutions.

Senior Data Engineers need to be adept in several technical and business skills. These include working with diverse datasets, parsing and understanding data, working with domain experts, data scientists and analysts in framing the business problems and provisioning integrated data quickly across multiple environments. Senior Data Engineers need to be inquisitive and motivated to learn modern technologies and capabilities which could benefit the organization and lead the effort in evaluating the technology for acceptance.

Senior Data Engineers also assist the business data science efforts with source data, building data sets, helping evaluate models and integrating analytics and data science model outputs into business processes.

• Hybrid cloud environment: the Senior Data Engineer works in a hybrid cloud ecosystem composed of Azure, Oracle and on‑premises technologies, building and supporting data and analytics solutions. The Senior Data Engineer will need to learn the data, tools and capabilities resident in this hybrid ecosystem, such as Synapse, Data Lakes, Dedicated Pool, Azure ML, SQL Server, SSIS and SSAS.
• Build data pipelines:
  Managed data pipelines consist of a series of stages through which data flows. Designing, building and maintaining data pipelines in Azure and the on‑premises ecosystems will be the primary responsibility of the data engineer.
• Drive data‑centric decision making:
  Assist with enhancing the data and metadata management infrastructure to ensure data quality, accessibility and security.
• Collaborate across departments:
  Collaborate with business data consumers of various skill levels, in refining their requirements for various data and analytics initiatives. This collaboration can lead to building enterprise data products, enabling data‑driven decision making.
• Lead, educate and train:
  Be curious and knowledgeable about innovative technologies and data initiatives. Research and propose data ingestion, preparation, integration and operationalization tools or techniques to aid these initiatives. Train team members, data consumers, data scientists and data analysts in these technologies and preparation techniques.
• Participate in ensuring compliance and governance during data use:
  Work with data governance teams (and information stewards within these teams) in building, vetting and promoting content that adheres to data governance and compliance initiatives.
• Become a data and analytics evangelist:
  The Senior Data Engineer is a blend of data and analytics “evangelist,” “guru” and “fixer.” This role promotes the available data and analytics capabilities and expertise to business unit leaders, educating them in leveraging these capabilities in achieving their business goals.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member…