Data Engineer

Job description: Data Engineer
Stealth venture led by team with experience scaling b2c and b2b2c businesses from $0 to >$150M in revenue and multiple successful seeks data engineer. Initial need is for project work of a few days to a few weeks, with potential to extend to full time role either leading the data analytics organization or as a member of it, depending on mutual interest. If you are looking for your next role, or are happy in your current role but want to put your toe in the water, this is a low risk way to start, and make a few $$ on a side-hustle in the process.

Near term project responsibilities: To discuss via phone call or meeting.
Setup data infrastructure and develop ETL to ingest data from various sources into unstructured and structured data storage. Establish replicable data production and ingestion process and maintain data pipeline.

Longer term role outline
Specific responsibilities and skills to be worked out depending on professional level and role in data and analytics organization, but the responsibilities for members of the team will map roughly onto the following elements:

- Build a capability that allows business users to dive deep into financial and user data with cutting-edge analytics and data insights.
- Interface closely with product, engineering and business teams, working to actionable end products and business solutions, not merely technical solutions.
- Build robust data pipelines responsible for the ingest of heterogenous data across the business into a unified data lake.
- Take on research projects to improve data processing, data governance and data delivery
- Build and ensure data tables can serve as the source of truth for various high-level priorities
- Create scripts to automate operational processes
- Work cross-functionally to define problem statements, collect data, and make recommendations
- Build data expertise and own data quality for allocated areas of ownership
- Work with data infrastructure to triage infra issues and drive to resolution
- ELT/ETL and Data architecture and development, analysis, design, functional/technical specifications, deployment, and testing of all things pertaining to the enterprise data warehouse.
- Perform source data analysis
- Perform various QA tasks as necessary

Longer term Skills may include some or all of following, depending on level desired:
- Expertise creating internal software, tools, and libraries in an Agile environment.
- Experience and familiarity with Python, AWS, Glue, Athena, EMR, SQL, Java, Hive, DynamoDB and similar tools
- Familiarity with best practices in data storage including partitioning, compression, schema evolution, security compliance and columnar layout
- Data modeling and/or AI. Experience in building predictive models based on multivariate data sets. Relevant areas of experience may include: credit risk or quantitative investment algorithms, media performance and media mix modeling, demand projections across time of day time of year for retail or eCommerce businesses, customer propensity modeling etc etc.
- Excellent problem-solving skills and understanding of computer science fundamentals
- Excellent communication skills
- Extensive experience with data quality, relational database, and have developed/maintained internal tools. Past experience with BI, reporting, and data mining.
- Data Visualization. Proven ability to make data tell a story with graphs or other forms of visualizations; experience with tools such as QlikView, Power BI, or Tableau.
- Innovation: this position requires a skilled lateral thinker, pulling insight from data and free-associating unique perspectives on problems.


Profile (Regardless of level):
- Experience working in a big data environment creating robust data pipelines and automation with proven track record of results.
- Comfort working in ambiguous start up environment, adjusting approaches and deliverables as new facts emerge.
- Strong work ethic, and genuine curiosity.
- Practical, practical, practical.
- Collaborative
- Confidence to speak up and articulate dissenting opinions to any level of organization, in a thoughtful and constructive manner.
- Confident enough to receive dissenting opinions from any level of organization in a thoughtful and constructive manner.
- A passion for problem solving and a desire to use data to not merely disrupt a multi-billion dollar industry, but empower individuals, communities and industry participants who have traditionally lacked power in their relations with large industry incumbents.
- Finally, a sense of humor, more humility than bravado, and a kind demeanor. Culture is a critical priority for this management team. A players who behave as A-holes need not apply.
About the recuiter
Member since Mar 14, 2020
Mindiaesh Mahar
from Saskatchewan, Canada

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Offer to work on this project closes in 90 days!
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