Senior Data Engineer/Analyst

TEKsystems•Newark, NJ

3d•$65 - $70•Hybrid

About The Position

Responsible for both advanced analysis and the design, implementation, and operation of production data pipelines, analytics-ready datasets, and powerful data visualizations. This individual translates business and analytics requirements into robust data models and reliable ETL/ELT processes, mentors analysts and junior engineers, and ensures datasets meet quality, security, and performance expectations. Interacts directly with internal and external stakeholders in the development of reporting and analytic solutions.

Requirements

Advanced knowledge of analytics, reporting, scripting, and ETL/ELT tools and methodologies.
Strong proficiency in Python and data engineering frameworks/libraries such as PySpark and Pandas.
Strong proficiency in SQL and large-scale data warehouse environments.
Experience with modern cloud data platforms such as Snowflake and Databricks.
Proficiency with data visualization tools; Power BI and Sigma preferred.
Experience developing and orchestrating data pipelines using Airflow.
Experience working with large and complex datasets from multiple sources.
Strong understanding of relational databases, data warehousing concepts, and data modeling best practices.
Experience leveraging AI tools to support data pipeline development and management.
Strong understanding of business operations and performance metrics; experience with industry-specific metrics is a plus.
Ability to communicate technical concepts and analytical findings clearly to non-technical stakeholders.
Experience leading projects and collaborating effectively across multiple teams and organizational levels.
Strong analytical, problem-solving, critical-thinking, and project management skills.
Ability to investigate technical issues deeply and identify practical solutions.
Capable of managing multiple priorities and projects simultaneously in a fast-paced environment.
Demonstrated ability to contribute positively to team goals and foster a collaborative environment.
Experience assessing project data needs and ensuring the quality and integrity of data assets.
Strong Microsoft Office skills, including advanced Excel, pivot tables, data visualization, and PowerPoint.
Master's degree preferred in Computer Science, Data Science, Statistics, Engineering, or a related field, with relevant business experience.
5-10 years of experience in data engineering, analytics, or related disciplines.
Advanced SQL programming experience within large-scale data warehouse environments.
Experience designing and supporting ETL/ELT processes in modern cloud or big data environments such as Snowflake, Databricks, or similar platforms.

Nice To Haves

Experience with dbt is a plus.

Responsibilities

Responsible for improvements and maintenance of analytics and reporting infrastructure, including data warehouses, data lakes, and data pipelines.
Lead the design and development of real-time data ingestion projects, collaborating with engineers to deploy API functionality in Snowflake.
Create and manage data pipelines using Python and Airflow, automating repetitive tasks and improving operational efficiency.
Establish and maintain data governance practices, including version control and separate test and production environments, to ensure data accuracy, security, and compliance.
Design and implement strategic roadmaps for infrastructure and analytics development to support organizational objectives.
Collaborate with business partners and internal teams to design and develop reporting solutions and analytical studies that support key business initiatives.
Develop, validate, and execute complex SQL queries; create detailed reports and analyses to answer business questions, interpret results, and provide actionable recommendations.
Manage data engineering project plans and timelines, ensuring high-quality and timely deliverables.
Evaluate data requirements for assigned projects, ensuring data integrity, suitability, and alignment with business objectives.
Transform data into actionable insights through reports, dashboards, and analytics solutions, presenting findings to stakeholders.
Define and standardize metrics in collaboration with business partners and subject matter experts to facilitate accurate and consistent reporting.
Troubleshoot technical issues and data-related challenges, ensuring seamless operations and data accuracy.
Mentor junior analysts and engineers by providing technical guidance, resolving complex issues, and supporting professional development.
Build productive relationships with vendor and technology partners to optimize systems and identify improvement opportunities.
Apply statistical methods and analytical techniques to derive business insights, including analysis of geospatial data where applicable.
Lead advanced analytics initiatives by incorporating external data sources and developing AI/ML use cases that enhance data-driven decision-making.
Explore and implement innovative AI and machine learning solutions to improve analytics capabilities and business outcomes.