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Data Engineer
SolarEdge Technologies. Build and maintain large-scale training datasets from diverse sources .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and maintaining large-scale data pipelines and training datasets, ensuring data quality and integrity while collaborating with researchers to support model development and experimentation. Proficient in Python programming and experienced with cloud-based data processing and orchestration tools.
Highest-signal resume keywords
Python ProgrammingETL/ELT Pipeline DevelopmentData Quality ValidationAWS ServicesWorkflow Orchestration
ATS Keywords
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Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data EngineeringSQLData ModelingSchema DesignFeature CreationData TransformationData StorageDistributed ComputingData Manipulation LibrariesBatch Job Support
Soft Skills
Ownership MentalityCollaboration
Tools & Technologies
PandasAirflowSparkDaskRayS3AWS LambdaAWS SageMakerVerticaCassandra
Industry Keywords
Data QualityData IntegrityModel DeploymentForecast GenerationExperiment Infrastructure
Tech Stack
Tools & technologiesAirflowAWSCassandraCloudETLMySQLPandasPythonRayRedisSparkSQL
About the role
Key responsibilities & impact- Build and maintain large-scale training datasets from diverse sources
- Collaborate with algorithm researchers to understand data requirements and deliver well-structured inputs for experimentation and model development
- Build and maintain robust data pipelines for ingestion, feature creation, transformation, and storage
- Ensure reliable and scalable data access 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 pipelines and systems
- Enable early detection of shifts or anomalies affecting forecasts, model training, or online inference
- Support experiment infrastructure, including batch jobs, simulation workflows, and evaluation pipelines
Requirements
What you’ll need- 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
- Experience building production-grade ETL/ELT pipelines
- Experience with Pandas, Polars or other data manipulation libraries
- Experience with modern cloud or distributed data-processing ecosystems
- Experience with object storage such as S3 or equivalent
- Experience with workflow orchestration such as Airflow
- Experience with distributed computing frameworks such as Spark, Dask, Ray, or similar
- Experience with data modeling, schema design, efficient storage formats, partitioning strategies, and analytics and ML-ready datasets
- Strong proficiency in SQL
- Experience with relational, key-value, columnar, and time-series databases, such as Vertica, Cassandra, MySQL, and Redis
- Experience with AWS services such as S3, SageMaker, Lambda, and related tools
- Strong ownership mentality and willingness to tackle knowledge gaps and see projects through end-to-end
Benefits
Comp & perks- 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