Data Engineer

Reposted Yesterday
2 Locations
In-Office or Remote
Senior level
Semiconductor • Energy
The Role
As a Senior Data Engineer, you will build and maintain data pipelines, support machine learning models, and ensure data quality for SolarEdge's platforms.
Summary Generated by Built In

Are you ready to power the future?

At SolarEdge (NASDAQ: SEDG), we're a global leader in smart energy technology, with over 4,000 employees, offices in 34 countries, and millions of installations worldwide. 

Our innovative solutions include solar inverters, battery storage, backup systems, EV charging, and AI-based energy management. We're committed to making clean, green energy the primary power source for homes, businesses, and beyond. 

With the growing demand for electricity, the need for smart, clean energy sources is constantly rising. SolarEdge offers amazing opportunities to develop your skills in a multidisciplinary environment, covering everything from research and development to production and customer supply. Work with talented colleagues, tackle exciting challenges, and help create a sustainable future in an industry that's always evolving and innovating. Join us and be part of a company that values creativity, agility, and impactful work. 

Our AI & Algorithms group builds the intelligence behind our products, from predictive analytics and optimization to advanced models and Generative AI.

As a Senior Data Engineer, you will collaborate with researchers and engineers to build advanced data pipelines and infrastructure that enable machine learning models and drive research across SolarEdge platforms.

What will you be doing:

  • Build and maintain large-scale training dataset diverse sources.
  • Work closely with algorithm researchers to understand data requirements and deliver well-structured inputs that support experimentation and model development.
  • Build and maintain robust data pipelines that handle ingestion, feature creation, transformation, and storage, ensuring reliable and scalable access to data for modeling, research experiments, forecast generation, and online model deployment.
  • Establish best practices for versioning, reproducibility, metadata, lineage, and data quality validation.
  • Build internal Python utilities, APIs, and libraries to simplify data access for researchers.
  • Ensure data quality, integrity, and continuity across all pipelines and systems, enabling early detection of shifts or anomalies that could impact forecasts, model training, or online inference.
  • Support the team’s experiment infrastructure, including batch jobs, simulation workflows, and evaluation pipelines.

Requirements:

  • BSc in Computer Science, Data Engineering, or a related field.
  • At least 5 years of software engineering experience, including a minimum of 3 years in data engineering.
  • Strong programming skills, particularly in Python, and experience building production-grade ETL/ELT pipelines.
  • Experience with modern cloud or distributed data-processing ecosystems, including object storage (e.g., S3 or equivalent), workflow orchestration (e.g., Airflow), and distributed computer frameworks (Spark, Dask, Ray, or similar).
  • Experience with data modeling, schema design, efficient storage formats (e.g., columnar), partitioning strategies, and best practices for analytics and ML-ready datasets.
  • Strong proficiency in SQL and experience with a variety of database technologies, including relational, key-value, columnar, and time-series databases (e.g., Vertica, Cassandra, MySQL, Redis).
  • Experience with AWS services for data ingestion, storage, processing, and machine learning, such as S3, SageMaker, Lambda, and related tools.
  • Strong ownership mentality, willing to tackle gaps in knowledge and see projects through end-to-end;

Advantages:

  • MSc/PhD in Computer Science, Engineering, or related field.
  • Experience with time-series, sensor, IoT, or telemetry data.
  • Hands-on experience with distributed systems and cloud-native architectures (Kubernetes, Docker, hybrid/on-prem architectures).
  • Experience with streaming data platforms such as Kafka or Kafka Streams;

SolarEdge Offers: 

  • Excellent remuneration and benefits package
  • Day to day usage of cutting-edge technologies
  • High-level medical insurance
  • Extended annual leave
  • Professional development
  • Great supporting team and environment
  • Being part of a global function and global knowledge-sharing
  • Hybrid model of work - twice per week work at the office

Only short-listed candidates will be contacted.

SolarEdge recognizes its talented and diverse workforce as a key competitive advantage. Our business success is a reflection of the quality and skill of our people. SolarEdge is committed to seeking out and retaining the finest human talent to ensure top business growth and performance. 

Top Skills

Airflow
AWS
Cassandra
Dask
Docker
Kafka
Kubernetes
Lambda
MySQL
Python
Ray
Redis
S3
Sagemaker
Spark
SQL
Vertica
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The Company
HQ: Herzliya
3,234 Employees
Year Founded: 2006

What We Do

SolarEdge is a global leader in smart energy technology. By leveraging world-class engineering capabilities and with a relentless focus on innovation, SolarEdge creates smart energy solutions that power our lives and drive future progress.
Established in 2006, SolarEdge developed the DC optimized inverter solution that changed the way power is harvested and managed in photovoltaic (PV) systems. The SolarEdge intelligent inverter solution maximizes power generation while lowering the cost of energy produced by the PV system, for improved RoI.
Continuing to advance smart energy, SolarEdge addresses a broad range of energy market segments through its diversified product offering, including residential, commercial and large scale PV, battery storage and backup solutions, EV charging, home energy management, grid services and virtual power plants, and uninterrupted power supply (UPS) solutions

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