Big Data Developer

3 weeks ago

Delhi, India Hireologist Full time
Job Title:
Big Data Engineer
Location:
Pune (Hybrid)
Experience
- 5-7 YOE
Salary Range:
₹35–40 LPA
About the Role
We are looking for a
Big Data Engineer
to design, build, and scale high-performance data pipelines that power our products and insights. You’ll be working closely with product managers, architects, and engineering leads to define technical strategies and ensure the availability, reliability, and quality of data across the organization. This is a high-impact individual contributor role with ownership of critical data components and the opportunity to shape our evolving data platform.
Key Responsibilities
Design, build, and maintain robust data pipelines (batch and streaming) from diverse data sources.
Ensure high data quality, reliability, and availability throughout the pipeline lifecycle.
Collaborate with cross-functional teams to define technical strategy and deliver data-driven solutions.
Participate in code reviews, testing, and deployment to uphold engineering best practices.
Own and manage smaller components of the data platform with end-to-end responsibility.
Identify and resolve performance bottlenecks to optimize data pipelines.
Proactively explore and adopt new technologies, contributing as a senior individual contributor across multiple products and features.
Required Qualifications
5–7 years of experience in Big Data or Data Engineering roles.
Strong programming skills in
Java or Scala
(Python acceptable with solid Big Data experience).
Hands-on experience with distributed processing and streaming frameworks such as
Apache Spark, Kafka, Flink .
Experience with orchestration tools like
Airflow
(or equivalent).
Familiarity with cloud platforms ( AWS, GCP, Azure ) and services such as
S3, Glue, BigQuery, EMR .
Solid understanding of data structures, algorithms, and object-oriented programming.
Proven ability to write clean, efficient, and maintainable code.
Tooling & Ecosystem
Proficiency with version control (e.g., Git) and CI/CD tools.
Experience with data orchestration frameworks (Airflow, Dagster, etc.).
Understanding of common file formats:
Parquet, Avro, ORC, JSON .
Basic exposure to containerization ( Docker ) and infrastructure-as-code ( Terraform
a plus).

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