Senior Data Engineer – Data Analytics & BI

Accountabilities

• • Triage requests for people data, reporting, and ad hoc analysis, prioritize work, and communicate realistic delivery expectations to stakeholders.

  • Design, develop, automate, and maintain scalable ETL/ELT pipelines that ingest, transform, validate, and deliver data from diverse internal and external sources.

  • Build self-service reports, dashboards, and data visualizations that communicate meaningful KPIs and enable leaders to identify insights and make informed decisions.

  • Partner with stakeholders to define reporting requirements and continuously improve core dashboards, analytics solutions, and data products.

  • Use SQL, Python, Tableau, Jupyter Notebook, and related technologies to extract, organize, analyze, and visualize data from multiple sources.

  • Collaborate with Data Engineering, Data Science, and other cross-functional teams to apply effective practices in data collection, pipeline architecture, analytics, and solution development.

  • Audit data integrity, investigate data-quality issues, and establish processes that improve the accuracy, consistency, and reliability of reporting and analytics.

  • Optimize ETL processes through effective architecture, code optimization, and performance improvements.

  • Provide guidance and coaching to end users on interpreting metrics, using dashboards, and applying data effectively.

  • Document reporting requirements, technical designs, data definitions, operational procedures, and changes to analytics solutions.

  • Participate in on-call responsibilities, monitoring data systems and responding to operational issues to maintain reliability and uptime.

  • Stay current with emerging data engineering practices, analytics technologies, cloud platforms, and industry trends.

  Requirements:

  • 8+ years of professional experience with SQL, including complex query optimization and large-scale relational and columnar databases.

  • 5+ years of hands-on Python experience focused on data engineering, including pipeline development, automation, and data transformation.

  • 8+ years of experience developing custom reports, dashboards, and visualizations using Tableau or comparable business intelligence tools.

  • Strong experience with data management, including validating, auditing, and reconciling data and reports across multiple systems.

  • Hands-on experience with cloud-based data platforms such as AWS, Azure, or Google Cloud Platform, as well as distributed technologies such as Spark or Hadoop.

  • Strong knowledge of relational database systems and familiarity with NoSQL technologies such as MongoDB or Cassandra.

  • Experience with data orchestration and transformation tools such as Apache Airflow and dbt.

  • Experience with Apache Hive and Presto for large-scale distributed query processing.

  • Experience supporting large-scale data migration initiatives, including requirements gathering, pipeline design, implementation, and operational support.

  • Familiarity with machine learning concepts, algorithms, and data science workflows.

  • Understanding of DevOps principles and their application to data management, deployment, and operational workflows.

  • Experience mentoring or coaching junior engineers and analysts.

  • Bachelor's or master's degree in computer science, mathematics, statistics, engineering, social sciences, physical sciences, or another discipline emphasizing data analysis and visualization, or equivalent professional experience.

  • Excellent communication and presentation skills, with the ability to explain technical concepts to non-technical audiences and collaborate effectively with stakeholders at all levels.

  • Strong technical documentation skills, including the ability to create design specifications, runbooks, data dictionaries, and other technical materials.

  • Comfortable working in ambiguous, fast-paced environments and shifting between strategic initiatives and tactical analytics requests.

  • A strong commitment to engineering excellence, including thorough testing, clear documentation, maintainable solutions, and a "do it the right way" mindset.

  • Ability to work effectively with distributed teams and communicate through remote collaboration and video-conferencing tools.

  Benefits:

  • Competitive compensation, with the role advertised at approximately $135,000.

  • Remote work environment.

  • Opportunities for continuous professional development and training.

  • Access to learning opportunities and industry certifications.

  • Collaboration with experienced data, engineering, analytics, and technology professionals.

  • Comprehensive benefits designed to support employees' professional and personal well-being.

  • A collaborative and inclusive work environment focused on professional growth.

  • Opportunities to work on large-scale data, analytics, cloud, and business intelligence initiatives.

  • A culture that emphasizes continuous learning, teamwork, inclusion, and employee development.