Data engineer

Job Description

P3-C3-TSTSBechtel Corporation is seeking talented and ambitious big data engineer to join our Big Data and A.I. Center of Excellence (BDAC) team. BDAC designs, develops, and deploys industry-leading data science and big data engineering solutions, using Artificial Intelligence (AI), Machine Learning (ML), and big data platforms and technologies, to increase efficiency in the complex work processes, enable and empower data-driven decision making, planning, and execution throughout the lifecycle of projects, and improve outcomes to Bechtel organization and its customers. Who you are:You yearn to be part of groundbreaking projects that work to deliver world-class solutions on schedule. Someone who is motivated to find opportunity in and develop solutions for evolving challenges, is passionate about their craft, and driven to deliver exceptional results. You love to learn modern technologies and guide other engineers to raise the bar on your team. You are imaginative and engaged about intuitive user interfaces, as well as new/emerging concepts and techniques. Job Responsibilities:Big data design and analysis, data modeling, development, deployment, and CICD operations of big data pipelines Collaborate with a team of other data engineers, data scientists, and business subject matter experts to process data and prepare data sources. Mentor other data engineers to develop a world class data engineering team. Ingest, Process, and Model data from heterogeneous data sources to support Data Science projects. Basic Qualifications:Bachelors degree or higher in Computer Science, or equivalent degree and 3-10 years related working experience. In-depth experience with a big data cloud platform, preferably Azure. Strong grasp of programming languages (Python, PySpark, or equivalent) and a willingness to learn new ones. Experience writing database-heavy services or APIs. Experience building and optimizing data pipelines, architectures, and data sets. Working knowledge of queueing, stream processing, and highly scalable data stores Experience working with and supporting cross-functional teams. Strong understanding of structuring code for testability. Preferred Qualifications:Professional experience implementing and maintaining MLOps pipelines in MLflow or AzureML. Professional experience implementing data ingestion pipelines using Data Factory. Professional experience with Databricks and coding with notebooks. Professional experience processing and manipulating data using SQL and Python code. Professional experience with user training, customer support, and coordination with cross-functional teams.