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Senior Data Engineer
4 months ago
We are building our core Data Team, as a Data Engineer, you will play a crucial role in building foundational datasets, designing pipelines, and developing the infrastructure to support them. Your work will accelerate decision-making processes for key project and business functions. If you're passionate about analytics, data models, and solving complex data problems, then this is the team for you
A DAY IN THE LIFE
- Define processes and ETL infrastructure to transform and make data readily available across the company.
- Build core datasets to serve as unique sources of truth for various business functions including project management, estimating, procurement, finance, operations, and engineering.
- Partner with project managers, business leaders, and internal stakeholders to understand their needs and design, build, and monitor pipelines that meet current requirements while also scaling gracefully with our growing data size.
- Implement automated workflows to reduce manual/operational costs for stakeholders, define and uphold SLAs for timely data delivery, and move the company closer to democratizing data and a self-serve model (query exploration, dashboards, data catalog, data discovery).
NECESSARY QUALIFICATIONS
- Self-starter mentality with the ability to gather and synthesize high-impact needs from business partners, design and implement technical solutions, and effectively communicate deliverables, timelines, and trade-offs.
- 5-7 years of experience as a data engineer building core datasets and supporting business verticals as needed. Passionate about analytics use cases, data models, and solving complex data problems.
- Hands-on experience shipping scalable data solutions in the Azure Cloud (e.g., AWS, GCP, Azure), across multiple data stores (e.g., Snowflake, Redshift, Hive, SQL/NoSQL, columnar storage formats), and methodologies (e.g., dimensional modeling, data marts, star/snowflake schemas).
- SQL expertise with an understanding of aggregation functions, window functions, UDFs, self-joins, partitioning, and clustering approaches to run correct and highly-performant queries.
- Highly comfortable with object-oriented programming paradigms (e.g., Python, Java, Scala).
- Experience working at a fast-growing company, a construction company, or eagerness to contribute in such an environment (Preferred).
- Hands-on experience in designing and building highly scalable and reliable data pipelines using Big Data stack (e.g., Airflow, Azure Data Pipeline, Spark, Hive, Parquet/ORC, Protobuf/Thrift, etc.) (Preferred).