The company is looking to advance its data-driven decision-making capabilities by designing, building, and maintaining systems and infrastructure for data storage, processing, and analysis. The goal is to generate insights from connected data and accelerate the productivity of engineering, analyst, and data scientist teams.
Requirements
- Experience in building data pipelines and deploying/maintaining them following modern DE best practices -target tech stack: Python OSS Data Ecosystem (PySpark, pandas, Dash); knowledge of SQL, DBT is a plus
- Heavy experience with Azure Data Factory is a must.
- Experience with designing and maintaining data warehouses and/or data lakes with big data technologies such as Spark/Databricks, or distributed databases, like Redshift and Snowflake, and experience with housing,accessing, and transforming data in a variety of relational databases
- Software Engineering fundamentals and software development tooling (e.g., Git, CI/CD, JIRA) and familiarity with the Linux operating system and the Bash/Z shell
- Experience with cloud database technologies (e.g., Azure) and developing solutions on cloud computing services and infrastructure in the data and analytics space
- Basic familiarity with BI tools (e.g., Alteryx, Tableau, Power BI, Looker)
- Experience working in data engineering or data architect role
Responsibilities
- Designs, develops, optimizes, and maintains data architecture and pipelines that adhere to ELT principles and business goals.
- Creates data products for engineer, analyst, and data scientist team members to accelerate their productivity.
- Engineer effective features for modelling in close collaboration with data scientists and businesses.
- Leads the evaluation, implementation and deployment of emerging tools and process for analytics data engineering in order to improve productivity as a team and quality.
- Partners with machine learning engineers, BI, and solutions architects to develop technical architectures for strategic enterprise projects and initiatives.
- Fosters a culture of sharing, re-use, design for scale stability, and operational efficiency of data and analytical solutions.
- Advises, consults, mentors, and coach other data and analytic professionals on data standards and practices.
Other
- The data engineer will work with a multidisciplinary Agile team
- Strong understanding of agile methodologies and experience as a Data Engineer on a cross-functional agile team preferred
- Learns about machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics as necessary to carry out role effectively.
- Develops and delivers communication and education plans on analytic data engineering capabilities, standards, and processes.
- 3+ years of experience as a Data Engineer, preferably in a large organization
