Data Engineer
Brooksource
Fortune 500 Utility Client
Downtown Houston, TX
Our client is scaling their Analytics organization and creating specialized verticals based on business unit. They need a senior-level Data Engineer to join the group that does Analytics Enablement for these verticals who will build data sets from unstructured sources to solve business problems. Ideally, this individual will have at least 5 years' experience in a data-related role, be an expert with SQL, and have familiarity with Big Query, Google Cloud, and Python.
If you think you could be a fit, keep reading and apply!
To be successful in this role you will:
- Collaborate with business stakeholders to understand their needs and translate them into actionable insights and data-driven solutions.
- Perform data analysis tasks, including data cleaning, data transformation, and data visualization, to uncover meaningful patterns and trends in large datasets.
- Partner with data engineering to develop and maintain data pipelines and workflows, ensuring efficient and accurate data extraction, transformation, and loading (ETL) processes.
- Apply statistical analysis techniques and machine learning algorithms to identify correlations, predict outcomes, and optimize business processes.
- Assist in the development and maintenance of data models, data dictionaries, and data documentation to ensure data integrity and consistency.
- Conduct exploratory data analysis to discover insights and provide recommendations for improving business performance and decision-making.
- Collaborate with data engineers and data scientists to identify opportunities for automation and optimization of data processes and workflows.
- Monitor data quality and proactively identify and resolve data discrepancies or anomalies.
- Participate in cross-functional teams to support data-related projects, providing expertise and guidance on data analysis, data management, and data visualization.
- Work on business case development, project value proposition, and help with workload prioritization.
- Stay updated with the latest industry trends and advancements in data analytics, data science, and data engineering, and apply this knowledge to enhance data capabilities within the organization.
- Constant, initiative-taking pursuit of learning systems, organizational structure, processes, data sets, techniques, etc.
- Interpret and explain information to audiences who are not familiar with the subject matter, often requiring persuasion.
- Is required to review and recommend solutions to issues that involve a number of alternatives which may not be clearly defined.
- Serve as a project lead or task force member on projects and/or issues having a significant impact on functional and strategic goals.
- Provide guidance and training to others in the use of innovative technologies, theories, concepts, and techniques.
- Operate with limited supervision, guidance, and direction from leadership and senior staff.
Top skills:
- Requires a bachelor’s degree from an accredited college or university in Data Science, Analytics, Mathematics, Statistics, Computer Science, or a related field.
- Requires a minimum of five (5) years of related experience.
- Strong proficiency in Data visualization software like PowerBI, Tableau, and Looker.
- Strong proficiency in Cloud Computing Platforms such as GCP, Azure, and AWS.
- Experience with Data Warehousing technology like Oracle Databases, SAP HANA, Google Big Query.
- Strong proficiency in SQL for data querying and manipulation.
- Strong in programming languages such as Python and R for data analysis and scripting.
- Understanding of data modeling concepts and experience with data modeling tools.
- Experience working with machine learning, statistical techniques, and algorithms.
- Proficiency in ETL processes, data warehousing, and database management systems.
- Excellent problem-solving and analytical skills, with diligence.
- Experience interacting with employees of all levels to present technical data in a non-technical manner.
- Effective communication skills, with the ability to translate complex data concepts into understandable insights for non-technical stakeholders.
A bonus to have:
- Experience with spatial analytics and GIS tools like ESRI.
- Project management experience.
- Utility experience.
- Experience with data governance.
