About the Role
We are looking for a Big Data Engineer to design, build, and operate large-scale data pipelines and analytical infrastructure that transform high-volume raw data into reliable, query-ready datasets for analytics, reporting, and data-driven products.
Our data platform ingests and processes data from multiple sources and serves analytics, data science, product, and downstream applications. In this role, you will own data pipelines end-to-end—from ingestion and transformation to warehousing, orchestration, data quality, and observability.
A key part of the role is owning ClickHouse as our primary analytical data store. You will be responsible for designing scalable data models, optimizing query performance, and ensuring the platform remains reliable and cost-productive as data volumes and workloads grow.
You will work closely with data scientists, analysts, product engineers, and other engineering teams to build a modern, cloud-native data platform.
What You'll Do
Design, build,
and maintain robust batch and streaming data pipelines that ingest data from multiple sources into analytical data stores.
Build and operate Apache Airflow DAGs, including scheduling, dependencies, retries, backfills, idempotency, concurrency, and failure handling.
Develop analytics-ready datasets using dbt, following well-structured staging, intermediate, and mart layers with appropriate tests, documentation, and incremental models.
Own ClickHouse as the primary analytical store, including:
Schema and table design using the MergeTree family of engines
Partitioning and sorting/primary key strategies
Materialized views
Distributed and replicated table architectures
Query and memory optimization
High-volume data ingestion and performance tuning
Work with BigQuery where cloud data-warehouse patterns are appropriate, including data modeling and query/cost optimization.
Design and operate NoSQL and key-value data stores, including Bigtable, DynamoDB, and Redis, based on specific acces
📌 Big Data Engineer (India)
🏢 Wingify
📍 India