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Staff Data Engineer

unlimited holidays

Remote:

Hybrid

Contract:

Full time

Experience:

Expert & Leadership (>10 years)

Work from:

Alpharetta (US), Houston (US)

Offer summary

Qualifications:

10+ years of software engineering experience, 5+ years in data engineering, Expertise in Python, SQL, database design, and data modeling.

Key responsabilities:

Build, test, and scale data ingestion pipelines for energy market data platform
Develop systems for processing data efficiently, collaborate with teams on technical solutions
Own data frameworks, troubleshoot data pipelines, and define data management strategy

Fluence Sustainable development Large https://fluenceenergy.com/

1001 - 5000 Employees

See more Fluence offers

Job description

This position will be supporting the Fluence Mosaic team. Fluence Mosaic team’s software technology uses artificial intelligence, advanced price forecasting, portfolio optimization and market bidding to ensure energy storage and flexible generation assets are responding optimally to price signals sent by the market.

You will be an integral member of the Fluence Mosaic team, maturing, developing, and maintaining a data ingestion and storage platform which serves our trading, forecasting, reporting, and analytical applications.

The position will be based in Fluence’s Houston office, with close interaction with a global team of data scientists, product managers, and subject matter experts to shape the evolution of our company and the future of the electricity grid.

What does a Staff Data Engineer do at Fluence?

Build, test, scale, and refine data ingestion pipelines across our energy market data platform

Design, develop, and maintain systems for querying and processing data, working with data scientists and software engineers to drive efficient solutions

Build and own data frameworks and libraries, supporting others in deploying, operating, and extending upon your clean, tested code

Help define our data story and enable data-driven solutions at Fluence Mosaic, both technically and culturally

Work with on-call staff, data scientists, software engineers and customer teams to trouble-shoot and debug data pipelines

Help define data management strategy.

What does the ideal candidate look like?

10+ years of professional software engineering experience with at least 5+ years of data engineering experience

Excellent written and verbal communication skills

Expert in Python, with hands on experience with data engineering tools such as Pandas

Knowledgeable in at least one other programming language (C/C++, Kotlin, Java) with the ability to adapt to new environments

Expert in SQL with a strong understanding of database design, data modeling, and query tuning with hands on experience ingesting, storing and serving time-series data preferred

Hands on knowledge of PostGres

Experience building Restful services

Understanding of automated testing

Experience with containerization technologies such as Docker

Experience on setting up deployment process, and tools

Knowledge of available data streaming platforms, distributed compute frameworks, and file storage formats with the expertise to apply their use to meet our organizational needs

Experience building data pipelines with stringent latency and correctness requirements

Hands on experience working with the AWS cloud and AWS services such as S3, Aurora, RDS, EC2, Lambdas, etc.

Strong computer science fundamentals, including knowledge of data structures and algorithms

Proven ability to meet deadlines and deliver solutions quickly at high quality

Passionate about learning, and tackling new and exciting technical challenges

Nice to haves:

Working knowledge with Terraform

Experience with BI tools such as Looker, PowerBI

Experience with vizualization tools in the python ecosystem such as matplotlib, plot.ly, etc

Experience working with Data Science teams

Experience working with data warehouses such as Snowflake

Experience with Cassandra or Scylla