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Job Summary:
Sargent & Lundy is a leading consulting engineering firm specializing in the power and energy sectors. They are looking for a motivated Data Engineer to enhance their data infrastructure and support analytics initiatives, collaborating with cross-functional teams and driving process improvements.
Responsibilities:
• Assist in the design, development, and maintenance of scalable data pipelines and ETL processes to ensure data accuracy and reliability across various internal systems and support analytics initiatives.
• Help integrate and manage various data sources, including cloud-based data platforms (AWS, Azure, Google Cloud).
• Participate in data architecture discussions to improve data reliability and scalability, working with data engineers to enhance infrastructure.
• Maintain thorough documentation of data engineering processes and workflows to ensure consistency and ease of knowledge transfer within the team.
• Lead post-mortems on data-related incidents, helping the team learn from past challenges and refine processes to prevent future issues.
• Collaborate with cross-functional teams to identify data needs and provide actionable insights.
• Partner with stakeholders to define and refine metrics that guide decision-making, helping teams across the organization make data-driven decisions.
• Work closely with data analysts, data scientists, and other stakeholders to provide reliable data access for analysis and ensure data availability and performance for different teams within the organization.
• Participate in cross-functional sprint planning to align data initiatives with broader company goals, ensuring that analytical work supports upcoming launches and projects.
• Facilitate regular data reviews with other teams, identifying gaps, inconsistencies, or emerging needs that could be addressed to improve business outcomes.
• Act as a liaison between business units and technical teams, translating business requirements into technical specifications that guide data-related projects.
• Contribute to company-wide data culture to increase awareness and understanding of data's impact.
• Monitor and ensure data quality by implementing validation checks, identifying data discrepancies, and advocating for data quality improvements across systems.
• Collaborate on data governance initiatives, working with security and compliance teams to ensure data privacy and adherence to regulatory requirements.
• Take ownership of data documentation, including definitions, data lineage, and best practices to promote data literacy across the organization.
• Leverage robotic process automation (RPA) and workflow automation tools (for example, Power Automate and Python scripts) to streamline repetitive operational tasks including reporting, data file transfers, compliance checks, and report generation.
• Develop monitoring and automated alerting solutions for data pipeline failures, data drift, and data quality issues, enabling proactive resolution and maintaining high data reliability.
• Collaborate with cross-functional teams to identify, design, and implement process automation opportunities across engineering design, reporting, project management, and documentation workflows, boosting efficiency with macros, scripting, and industry-standard automation tools.
• Engage in the mentoring and training of other analysts or non-technical stakeholders, enhancing their data skills and helping them grow professionally.
• Stay up-to-date on industry trends and best practices, identifying opportunities to implement new tools or techniques that benefit the entire data team.
• Support leadership in strategic planning, providing data-backed insights that help shape the company's direction and key objectives.
Qualifications:
Required:
• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field.
• At least 2 years of experience in a data engineering or similar role, including internships or co-op programs.
• Basic proficiency in SQL for querying databases and manipulating data.
• Familiarity with ETL tools and processes
• Experience with cloud platforms, such as AWS, Azure, or Google Cloud, for data storage and processing.
• Familiarity with Python or another programming language used for data manipulation and scripting.
• Strong attention to detail with a proactive approach to problem-solving.
• Ability to work collaboratively with cross-functional teams and communicate effectively with both technical and non-technical stakeholders.
• A willingness to learn and adapt to new technologies and methodologies in data engineering.
Company:
Sargent & Lundy is a power generated company that provides technical expertise and integration for global use. Founded in 1891, headquartered in Chicago, Illinois, USA, team size 1001-5000 employees, currently Late Stage.
