Data Engineer

Who we are:

Enterra Solutions is the leading Autonomous Decision Science™ company providing data-enabled prescriptive and anticipatory analytics and insights for companies across a broad range of industries. Enterra automates a new way of problem-solving and decision-making, going beyond advanced analytics to understand data, perform analytics, generate insights, answer queries, and make decisions at the speed of the market. This powerful capability uniquely enables “End-to-End Value Chain Optimization and Decision-Making” at scale and allows clients to uncover and understand the inter-relationships that lead to innovative new product development and innovation, heightened consumer understanding and targeted marketing, revenue growth tactics, and intelligent demand and supply-chain planning. We help transform market-leading companies into true data-driven digital enterprises.

What you will do:

The successful candidate will join a diverse team to: 

  • Build unique high-impact business solutions utilizing advanced technologies for use by world class clients.
  • Create and maintain the underlying data pipeline architecture for the solution offerings from raw client data to final solution output. 
  • Create, populate, and maintain data structures for machine learning and other analytics. 
  • Use quantitative and statistical methods to derive insights from data.
  • Guide the data technology stack used to build Enterra’s solution offerings.
  • Combine machine learning, artificial intelligence (ontologies, inference engines and rules) and natural language processing under a holistic vision to scale and transform businesses — across multiple functions and processes.

Responsibilities Include:

  • Work with other Enterra personnel to develop and enhance commercial quality solution offerings
    • Create and maintain optimal data pipeline architecture, incorporating data wrangling and Extract-Transform-Load (ETL) flows. 
    • Assemble large, complex data sets to meet analytical requirements – analytics tables, feature-engineering etc.
    • Build the infrastructure required for optimal, automated extraction, transformation, and loading of data from a wide variety of data sources using SQL and other ‘big data’ technologies such as Databricks.
    • Build automated analytics tools that utilize the data pipeline to derive actionable insights.
    • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
    • Design and develop data integrations and data quality framework.
    • Develop appropriate testing strategies and reports for the solution as well as data from external sources. 
    • Evaluate new technology for use within Enterra.
  • Work with other Enterra and client personnel to administer and operate client-specific instances of the Enterra solution offerings
    • Configure the data pipelines to accommodate client-specific requirements to onboard new clients.
    • Perform regular operations tasks to ingest new and changing data – implement automation where possible.
    • Implement processes and tools to monitor data quality – investigate and remedy any data-related issues in daily solution operations.


  • Bachelor’s degree in Computer Science or a STEM (Science, Technology, Engineering or Math) field required
  • Minimum of 3 years hands on experience as a data engineer or similar position.
  • Minimum of 3 years commercial experience with Python or Scala Programming Language
  • Minimum of 3 years SQL and experience working with relational databases (Postgres preferred).
  • Experience with at least one of the following – Databricks, Spark, Hadoop or Kafka
  • Demonstrable knowledge and experience developing data pipelines to automate data processing workflows
  • Demonstratable experience in data modeling
  • Demonstratable knowledge of data warehousing, business intelligence, and application data integration solutions 
  • Demonstratable experience in developing applications and services that run
    on a cloud infrastructure (Azure preferred)
  • Excellent problem-solving and communication skills

The following additional skills would be beneficial:

  • Knowledge of one or more of the following technologies: Data Science, Machine Learning, Natural Language Processing, Business Intelligence, and Data Visualization
  • Knowledge of statistics and experience using statistical or BI packages for analyzing large datasets (Excel, R, Python, Power BI, Tableau etc.)
  • Experience with container management and deployment, e.g., Docker and Kubernetes