NatPower is a global group specialised in renewable energy assets development, with operations in several countries. We are launching in the UK market, aiming at becoming one of the leaders in the next 3-5 years as it successfully did in other geographies.
We are looking to hire a Data and Automation Engineer, with the hybrid working option, to join our team to support and assist the Development Team of a group on various projects across the UK.
All our projects are at the early development stage so you will be collaborating with teams from initial site feasibility, right through to ready-to-build. As we grow, we will also be expanding into new markets and there will be opportunities to contribute to this expansion.
The role will be part of a very impressive senior ICT team with some of the strongest track records in the software development sector, affording an excellent opportunity to learn and advance your career. You will need to be ready to work in a flexible environment where everyone is aligned with company development.
The Data and Automation Engineer will support various teams across the NatPower UK Development but will work closely with the Chief Information Officer in delivering the development of solutions for renewables projects across the UK and will be directly responsible for the development and deployment of data pipelines. The developer will set up and own day-to-day management of the Database Automation pipeline while working closely with various stakeholders. You as a middleware developer will work at the intersection of data analysis, data automation, middleware, and UX flow. The primary duties will include requirement gathering and analysis, and stakeholder engagement for the data automation of project/s. You as a Data Engineer will be responsible for the complete maintenance and development of the database, including knowledge of ETL, Big Data, and pipeline deployment. You should be able to identify and solve problems creatively while keeping security and efficiency in mind.
We are looking for a multi-skilled candidate with a quantitative background for the position of Data Engineer with experience in pipeline design, automation, and deployment. The Data Engineer will be responsible for efficient, reusable well-designed, and high-quality stored procedures, and automation script to support frontend and middleware to access database/s.
The data engineer will need to present their findings to both technical and non-technical audiences is another important skill and being comfortable in written and verbal communication.
Humility coupled with a good sense of humor is high on our list of character traits.
Essentials:
· Experience in engineering new data pipelines, architectures, and data sets for optimizing the performance of existing data pipelines depended upon by production software applications.
· 5+ years of data engineering experience for big data, data analytics, reporting, and machine learning solutions with advanced SQL knowledge.
· Proficient in designing and developing data models for simulated and acquired data.
· Experience with Data Warehouse, Data Modelling, building data engineering pipelines for performance and scalability, automation of data flow, and building multiple unique but similar data pipelines to support specific test requirements.
· Experience in designing data pipelines to automate high-volume and real-time data delivery.
· Provide guidance to business and tech partners on the best methods to engineer data processes.
· Establish and drive DevOps techniques and practices, like Continuous Integration, Continuous Deployment, Build Automation, and Test-Driven Development to enable the rapid delivery of working code utilizing tools like Jenkins, Maven, Ansible, Git, and Docker.
· Experience with big data tools: Hadoop, Spark, Kafka, etc.
· Experience with relational SQL and NoSQL databases, particularly Postgres.
· Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
· Experience with AWS cloud services: EC2, EMR, RDS, Redshift.
· Experience with multiple data architecture paradigms (relational, non-structured, streaming)
· Knowledge of various data communication protocols (Rest API, GraphQL, RPCs, MQTT, AMQP)
· Experience with stream-processing systems: Storm, Spark-Streaming, etc.
· Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
· Experience using tools like Docker, Jenkins, and Kubernetes to deploy software.
· Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
Desirables:
· Experience in a Data Engineer or similar roles, who has attained a Bachelor’s degree in Bachelor’s degree in Engineering, Computer Science, Information Technology, related field, or equivalent work experience.
- Strong analytic skills related to working with unstructured datasets.
- Build processes supporting data transformation, data structures, metadata, dependency, and workload management.
- Understanding of AI/ML/Data Structure and knowledge of graph theory an advantage.
- Experience in GIS and spatial analysis is highly desirable.
· Strong SQL skills for spatial data management and PostGIS extension.
· Exposure to some geospatial tools/systems either commercial or open source.
- Experience in GIS-based technologies will be a bonus.
- Experience with code versioning tools such as Git.
- Excellent problem-solving and critical-thinking skills.
- Ability to work well in a team environment and collaborate with cross-functional teams.
· Able to manage several projects alongside one another.
· Ability to adapt to a fast-paced development schedule.
What's on Offer
· Base compensation: £ 60k – 70k depending on experience.
· Cash bonus as defined by the group policies.
· Benefits in line with NatPower UK policies.
· Probation period: 6 months
· Notice period: 3 months
· Starting date: ASAP
· We shall require references.
Job Activities Description
Some of these activities are performed by coordinating the work of external consultants or internal team members.
- Analysing organizational data requirements using agile methodologies UML.
- Automate analyses and authoring pipelines via SQL and ETL frameworks.
- Work with management to prioritize business and information needs.
- Acquire data from primary or secondary data sources and maintain databases/data systems to empower operational and exploratory analysis.
- Interpret complex data performance metrics, and analyse results using statistical techniques for reporting of observed patterns/trends.
· Building and deploying distributed automated data pipelines for various applications.
· Designing data flow/pipeline for data-intensive applications.
- Engaging with users to document user journeys and user experience.
- Design Data Warehouse, develop Data Models, deploy data engineering pipelines for performance and scalability, automate data flow, and build multiple unique but similar data pipelines to support specific test requirements.
· Plan and lead the development, testing, and deployment of data pipelines to meet user needs.
· Produce and own high-quality reliable data pipelines with a high degree of automation.