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.
- 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