About This Featured Opportunity
At Advantis Global, we are dedicated to connecting YOU to highly sought-after opportunities. Our client, a well-known Fortune 500 company in the Renewable Energy industry, is seeking an experienced Data Engineer to join their team. This is a fantastic opportunity to build and own large parts of the Onshore Wind Data Infrastructure. As a Data Engineer, you will be tasked with finding ways to improve scalability, reliability, and performance of critical data pipelines. You'll also be responsible for building, deploying, and managing data solutions and tools that drive analytics and insights across the business. In this role, you will collaborate closely with Data Scientists, Data Engineers, Analytics Engineers, Reliability Engineers, and Field Engineers to design, build, test, deploy, and run data-driven solutions. Additionally, you will play a key role in diagnosing and troubleshooting system failures using Root Cause Analysis (RCA) and Failure Mode and Effects Analysis (FMEA) methods. Join us in driving optimization, testing, and tool development to enhance the quality of our data products.
THE OPPORTUNITY FOR YOU
- Build and own large parts of Onshore Wind Data Infrastructure, focusing on scalability, reliability, and performance improvements for critical data pipelines.
- Deploy and manage data solutions and tools that support analytics and insights.
- Maintain and enhance toolsets, scripts, frameworks, and support Data Scientists and Analytics Engineers.
- Collaborate with cross-functional teams to design, build, test, deploy, and operate data-driven solutions.
- Utilize Root Cause Analysis (RCA) and Failure Mode and Effects Analysis (FMEA) to diagnose and troubleshoot system failures.
- Contribute to optimization, testing, and tool development to improve data product quality.
KEY SUCCESS FACTORS
- Strong teamwork and collaboration skills, with the ability to give and receive constructive feedback.
- Bachelor's or Master's degree in computer science, science, economics, statistics, mathematics, or equivalent practical experience in Data Engineering.
- Solid background in Data Modeling, Data Architecture, and Data Infrastructure Optimization.
- Minimum of 4 years of industry experience building, managing, and optimizing distributed data processing systems (e.g., Hadoop, Spark, Hive, Trino, Flink, Kafka, etc.).
- Proficiency in software engineering using languages like Python and Java to build scalable data solutions.
- Experience with both Relational databases (Postgres, MySQL, Oracle) and non-relational/analytics databases (Cassandra, MongoDB, Druid).
- Familiarity with open file formats (Parquet, JSON, ORC, etc.) and storage technologies (S3, Azure Blobstore, HDFS, etc.).
- Experience with modern data science toolsets such as Jupyter Notebook, Zeppelin, Superset, and Tensor Flow.
- Familiarity with software development practices like source control (Git), Test Driven Development, and Agile Analytics Development.
- Proficiency in deploying and managing solutions in the cloud (AWS, Azure, Google Cloud Platform).
- Experience with building, deploying, and managing solutions in a container environment (e.g., Docker, Kubernetes).
- Clear and concise communication skills to explain complex concepts.
- Passion for delivering superior customer experiences.
- Familiarity with implementing and managing security within data systems.
- Experience with system monitoring tools like Prometheus, New Relic, Elastic Stack, Grafana, etc.
- Ability to consume and create Web APIs (e.g., ReST, gRPC).
- Experience with deploying and managing search solutions like Solr/Elastic Search.
- Basic project management knowledge and skills.
- Company sponsored Health, Dental, and Vision coverage.
Advantis Global is an equal opportunity employer and makes employment decisions based on merit, qualifications, and abilities. Our company policy prohibits unlawful discrimination based on various characteristics. Additionally, we are committed to promoting pay equity and maintaining a harassment-free workplace for all employees.