Innowatts is an energy technology company based in Houston, TX that is transforming the way
energy is bought, sold, managed and consumed. We are a leading provider of AMI-enabled predictive
analytics and AI-based solutions for utilities, energy retailers, emerging retailers, and smart energy
communities. To date, the Innowatts eUtility™ technology platform has enabled over 52 million
energy consumers and their energy providers with access to lower energy costs and a more reliable
and personalized energy experience. Innowatts is backed by Energy Impact Partners, Shell Ventures,
Iberdrola Energy Ventures, Veronorte and Energy and Environment Investment (Japan).

Summary

As a Data Engineer you will develop and maintain scalable data pipelines while collaborating with
analytical and business teams to improve data models.

Responsibilities

Implements processes and systems to monitor data quality, ensuring production data is
always accurate and available for key stakeholders and business processes that depend on it.
Writes unit/integration tests, contributes to engineering wiki, and documents work.
Performs data analysis required to troubleshoot data related issues and assist in the
resolution of data issues.
Works closely with a team of frontend and backend engineers, product managers, and
analysts.
Defines company data assets (data models), and other jobs to populate data models.
Designs data integrations and data quality framework.
Designs and evaluates open source and vendor tools for data lineage.
Works closely with all business units and engineering teams to develop strategy for long
term data platform architecture.

Minimum Qualifications

Preferable to have a Degree in an analytical field (e.g. Computer Science, Mathematics,
Statistics, Engineering, Operations Research, Management Science) and 4+ years of
professional experience.
At least 4 years of data analytics experience in a distributed computing environment
Database maintenance
Building and analyzing dashboards and reports
Evaluating and defining metrics and perform exploratory analysis
Monitoring key product metrics and understanding root causes of changes in metrics
Empower and assist operation and product teams through building key data sets and data-
based recommendations
Automating analyses and authoring pipelines via SQL/python based ETL framework
Superb SQL programming skill
Understanding of ETL tools and database architecture
Advanced knowledge of data warehousing.
Strong knowledge of code and programming concepts. Experience with Python.
Experience with Kubernetes deployments and DevOps approach
Highly motivated self-starter who is flexible and goal oriented
Strong Python Knowledge
- Data Models
- Object-Oriented Programming
- Testing (Unit / Regression)
Database Experience
- Window Functions
- Partitioning/Indexes
- Relational and Non-Relational
Big Data Experience
- Hadoop
- Spark
- DataFrame API
Performance Benchmarking
- Cluster Configuration/Optimization
- Spark Optimzation
Version Control, CI/CD
- Git
- Jenkins, Drone
Some Cloud Experience
- AWS (primary), Azure, Google Cloud.
Nice to have
- Data Science Experience (Either direct or from working closely with a DS team)
- Scikit-Learn, Tensorflow, Spark.Mllib, General Algebra & Algorithms
- Airflow (Scheduling Tools)
- Container Experience : Docker, Kubernetes
- Streaming Experience : Kafka, Spark Streaming, Flink

Benefits and Additional Perks

Fast paced, collaborative and fun environment
Work with data and latest technology to transform industry
Competitive salary and bonus
Medical, dental, vision, 401k, life and long-term disability insurance
Paid Time Off
Hybrid working.

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