Data Engineer

AppSquadz; Dadri; On-site; INR 1,200,000 - 2,500,000; Full time

Job summary

AppSquadz seeks a Data Engineer / Analytics Engineer to design, build, and optimize scalable data pipelines on cloud platforms. You will work closely with business teams to transform raw data into reliable analytics-ready insights.

You will design Spark/PySpark ETL processes, manage AWS Glue and data lake ingestion, and develop dimensional models using Redshift/Athena. Collaboration with Product and Analytics teams is essential for KPI definitions and reporting.

Qualifications

• 2+ years of hands-on Python, SQL and Spark experience.
• Strong experience with AWS data services and data pipelines.
• Good knowledge of data warehousing and dimensional modeling.

Responsibilities

• Design and maintain Spark/PySpark-based ETL pipelines for high-volume batch and incremental data processing.
• Build and manage AWS Glue Jobs, Glue Crawlers, and S3-based data lake ingestion.
• Develop dimensional and fact-dimension models and maintain curated data marts using Redshift/Athena.
• Optimize SQL and Spark SQL queries for better performance and efficiency.
• Drive cloud cost optimization across storage, compute, and query usage.
• Build and maintain BI dashboards for revenue, engagement, and operational reporting.
• Handle ad-hoc data requests and convert business requirements into optimized queries and data models.
• Collaborate with Product, Business, and Analytics teams on data structures and KPI definitions.

Skills

Python

SQL

Spark/PySpark

Spark SQL

AWS

Redshift

Athena

Glue

Data Warehousing

Dimensional Modeling

Partitioning

Indexing

Query Optimization

Metabase

Matomo

Tools

AWS S3

AWS Redshift

AWS Athena

AWS Glue

CloudWatch

Job description

We’re looking for a Data Engineer / Analytics Engineer who can design, build, and optimize scalable data pipelines on cloud platforms and work closely with business teams to turn raw data into reliable, analytics-ready insights.

• Design and maintain Spark/PySpark-based ETL pipelines for high-volume batch and incremental data processing
• Build and manage AWS Glue Jobs, Glue Crawlers, and S3-based data lake ingestion
• Develop dimensional and fact-dimension models and maintain curated data marts using Redshift/Athena
• Optimize SQL and Spark SQL queries for better performance and efficiency
• Drive cloud cost optimization across storage, compute, and query usage using AWS Cost Explorer and CUR analysis
• Build and maintain BI dashboards for revenue, engagement, and operational reporting
• Handle ad-hoc data requests and convert business requirements into optimized queries and temporary data models
• Collaborate with Product, Business, and Analytics teams on data structures, reporting, and KPI definitions
• 2+ years of hands-on experience with Python, SQL, and Spark SQL/PySpark
• Strong experience with AWS S3, Redshift, Athena, Glue, and CloudWatch
• Good understanding of Data Warehousing and Dimensional Modeling
• Strong knowledge of Partitioning, Indexing, and Query Optimization
• Experience with BI/Analytics tools such as Metabase, Matomo, or similar platforms
• Proven experience in improving data pipeline performance and/or optimizing cloud costs

Nice to Have

• Experience in OTT/Streaming Media Analytics or Insurance/BFSI domains
• Experience with incremental data processing and near real-time pipelines
• Publications or applied research in Data Engineering

If you enjoy building scalable data solutions, solving complex data problems, and working with modern AWS data technologies, we’d love to hear from you!