Data Engineer at PowerLabs Inc

Role Overview

• As a Data Engineer, you will design, implement, and maintain data ingestion, storage, optimisation, processing (pre/post), and analytics pipelines for time-series IoT and energy data. 
• You will work closely with data scientists/analysts, software engineers, and optimisation experts to ensure seamless real-time and batch data workflow integration.

Required Skills & Qualifications

• 3+ years of experience in data engineering with a focus on IoT, energy, or industrial data.
• Proficiency in Python and SQL; experience with Scala is a plus.
• Experience building scalable ETL/ELT pipelines using Apache Airflow, NiFi, Prefect etc.
• Strong knowledge of distributed data processing frameworks (Dask, Spark, Flink, or Kafka Streams).
• Hands-on experience with both relational and NoSQL databases, including PostgreSQL, MySQL, Cassandra, DynamoDB, or MongoDB.
• Hands-on experience with time-series databases (TimescaleDB, InfluxDB, ClickHouse, or DuckDB).
• Familiarity with data lake architectures and formats (Apache Iceberg, Delta Lake, Parquet).
• Experience with cloud data services (AWS: S3, Glue, Lambda, Athena; GCP: BigQuery, Dataflow).
• Ability to optimise SQL queries and database performance.
• Experience in MLOps and data pipelines for ML workflows.
• Knowledge of energy systems, SCADA protocols, or grid optimisation is a plus.
• Strong problem-solving skills and ability to work in cross-functional teams.

Important

• This role is strictly not for vibe-coders.
• Do not apply if you rely more on guesswork than on clear data, prefer quick fixes over solid design, or value style over reliability.
• We need engineers who work carefully, follow strong processes, and deliver real, measurable results; anything less will not meet our standards.