AI Data Engineer 3 Days Left

2 days ago

Bengaluru, Karnataka, India Esko Full time
Job Description

We are seeking an AI Data Engineer to design, develop, and maintain scalable data pipelines for our analytics and AI workflows. The ideal candidate will be an expert in modern data orchestration, ETL/ELT frameworks, and distributed data processing. This role is crucial for ensuring the reliability, performance, and traceability of our data systems and for supporting our AI/ML teams.

Key Responsibilities

- Data Pipeline Development: Design, develop, and maintain resilient data pipelines using modern orchestration tools like Apache Airflow, dbt, Dagster, or Prefect.
- Data System Optimization: Build and optimize data lakes, data warehouses, and real-time data systems to support analytics, reporting, and AI workflows.
- Data Governance & Quality: Define and implement data modeling, schema evolution, governance, and quality standards across both structured and unstructured data sources.
- Collaboration & Support: Partner with our platform, product, and AI/ML teams to ensure the availability and performance of data systems in production.
- Best Practices: Drive the adoption of best practices in security, cost-efficiency, testing, and CI/CD for our data infrastructure.

Required Qualifications

- Education & Experience: A Bachelor's degree with 1-2 years of experience, or a Master's degree in Computer Science, Data Engineering, or a related field. Previous experience in data engineering or backend systems development is required.
- Technical Skills:
- Proficiency in distributed data processing tools like Spark, Flink, and Kafka Streams, and SQL engines such as Presto, Trino, BigQuery, and Snowflake.
- Deep understanding of data modeling, partitioning, columnar storage formats (Parquet, ORC), and schema design.
- Strong programming skills in Python, Java, or Scala.
- Familiarity with containerization and cloud infrastructure (AWS, GCP, or Azure).
- Work Style: Must be a stress-resilient team player who is comfortable working in an agile, MLOps-driven environment.
- Communication: You must have a strong command of the English language.

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