Data Engineer

ShyftLabs; Dadri; On-site; INR 900,000 - 1,500,000; Full time

Job summary

ShyftLabs is seeking a skilled Data Engineer to design and build scalable data platforms that power analytics, reporting, and business insights. You will develop high-performance batch and streaming pipelines, optimize ETL/ELT workflows, and manage large-scale analytical databases.

Collaborate with Product, Analytics, and Backend teams to deliver robust data solutions. The ideal candidate has strong SQL, experience with ClickHouse and cloud platforms, and a passion for turning data into

Qualifications

• 3+ years of experience in data engineering and building scalable data platforms.
• Strong SQL skills and query optimization.
• Experience with ClickHouse and other OLAP databases.
• Proficient in PostgreSQL.
• Experience building ETL/ELT pipelines.
• Proficiency in Java or Python.
• Experience with Apache Kafka and event-driven architectures.
• Cloud platform experience (AWS/GCP/Azure).
• Experience with Docker and Kubernetes.
• Knowledge of data modeling and partitioning strategies.
• Familiarity with monitoring/observability tools.

Responsibilities

• Design and build scalable batch and streaming data pipelines.
• Develop and optimize ETL/ELT workflows using distributed processing.
• Own and optimize ClickHouse clusters for large-scale workloads.
• Design efficient data models for reporting and dashboards.
• Build and maintain data ingestion pipelines from MongoDB, PostgreSQL, Kafka, APIs, and more.
• Improve performance of large SQL workloads and analytical queries.
• Build reliable monitoring, health checks, and data anomaly detection systems.
• Collaborate with Product, Analytics, and Backend teams for reliable reporting.

Skills

Data engineering

SQL

ClickHouse

PostgreSQL

ETL/ELT pipelines

Java or Python

Apache Kafka

Cloud platforms

Docker

Kubernetes

Data modeling

Monitoring/Observability

Tools

Looker

BigQuery

Redshift

Snowflake

Job description

Position Overview

We are seeking a skilled Data Engineer to design and build scalable data platforms that power analytics, reporting, and business-critical insights. You will develop high‑performance batch and streaming data pipelines, optimize ETL/ELT workflows, and manage large-scale analytical databases while ensuring data reliability and performance. This role requires strong expertise in SQL, distributed data processing, cloud technologies, and event‑driven architectures, along with close collaboration with Product, Analytics, and Backend teams to deliver robust data solutions.

At ShyftLabs, we live and breathe data. Since 2020, we’ve been helping Fortune 500 companies unlock growth with cutting‑edge digital solutions that transform industries and create measurable business impact. We’re growing fast and we’re looking for passionate problem‑solvers who are ready to turn big ideas into real outcomes.

Job Responsibilities

• Design and build scalable batch and streaming data pipelines.
• Develop and optimize ETL/ELT workflows using distributed data processing frameworks.
• Own and optimize ClickHouse clusters for large-scale analytical workloads.
• Design efficient data models for reporting and dashboarding use cases.
• Build and maintain data ingestion pipelines from MongoDB, PostgreSQL, Kafka, APIs, and other data sources.
• Improve performance of large SQL workloads and analytical queries.
• Build reliable monitoring, health checks, and data anomaly detection systems.
• Work closely with Product, Analytics, and Backend teams to deliver reliable reporting and insights.

Basic Qualifications

• 3+ years of experience in Data Engineering.
• Strong SQL skills with expertise in query optimization.
• Experience with ClickHouse or other OLAP databases (BigQuery, Redshift, Snowflake, Druid, Pinot, etc.).
• Strong knowledge of PostgreSQL.
• Experience building ETL/ELT pipelines.
• Proficiency in Java or Python.
• Experience with Apache Kafka and event‑driven architectures.
• Strong understanding of data modeling and partitioning strategies.
• Experience working on cloud platforms (AWS/GCP/Azure).
• Experience with Docker and Kubernetes.
• Knowledge of monitoring and observability tools.

Preferred Qualifications

• Experience with Looker or BI platforms.
• Experience with Apache Spark or Dataproc.
• Experience with Airflow or workflow orchestration tools.
• Understanding of advertising technology (DSP, RTB, Attribution, Campaign Reporting).
• Experience with large-scale analytical systems processing billions of records.

We are proud to offer a competitive salary alongside a strong insurance package. We pride ourselves on the growth of our employees, offering extensive learning and development resources.