Data Engineer

Role Overview

As a Data Engineer, you will be responsible for building and maintaining scalable data pipelines and architectures that enable AI and analytics solutions. You’ll work closely with data scientists, software engineers, and product teams to ensure data is clean, reliable, and ready for advanced modeling and insights.

What You’ll Do

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  Data Pipeline Development – Design, build, and maintain robust ETL/ELT pipelines for structured and unstructured data.

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  Data Integration – Ingest data from various sources (APIs, databases, cloud storage) into centralized data platforms.

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  Performance Optimization – Enhance data processing speed, reliability, and scalability.

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  Cloud Data Engineering – Work with cloud platforms (AWS, Azure, or GCP) for data storage, processing, and orchestration.

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  Collaboration – Partner with data scientists and analysts to ensure data availability and quality for downstream use cases.

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  Best Practices – Ensure code quality, data security, and maintainability through testing, automation, and documentation.

What Makes You Right for This Role

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  2–3 years of experience in data engineering, data warehousing, or big data environments.

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  Strong programming skills in Python or Java (experience with PySpark or Scala is a plus).

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  Hands-on experience with ETL tools and data pipeline frameworks (e.g., Airflow, Spark, Kafka).

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  Proficiency in working with SQL and relational databases (PostgreSQL, MySQL, etc.).

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  Familiarity with cloud platforms such as AWS (Glue, S3, Redshift), Azure (Data Factory, Synapse), or GCP (BigQuery, Dataflow).

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  Exposure to containerization (Docker, Kubernetes) and CI/CD workflows is a plus.

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  Passionate about data, automation, and building systems that drive intelligent decision-making.

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  Based in Chennai, with flexibility to collaborate with global teams.

Crayon Data Tech Stack

Java | Python | Spark | Kafka | Airflow |