Data Engineer

Actively Reviewing

Freight Tiger

Bengaluru Full-Time 4–8 yrs exp Posted 2 hours ago · Apply by Sep 16, 2026

Job Description

We are looking for a Data Engineer II (2–4 years of experience) to join our Data Platform Engineering team.

As a Data Engineer, you'll work on designing and building scalable data platforms capable of processing millions of logistics events every day. You'll help build reliable ingestion pipelines, optimize distributed data processing workloads, and develop curated datasets that power analytics, reporting, and AI-driven products across Freight Tiger.

This role offers an opportunity to work on modern cloud-native data technologies while solving complex engineering challenges at scale.

What You'll Do

Design, develop, and maintain scalable batch and streaming data pipelines.
Build reliable ingestion frameworks supporting CDC, incremental processing, and near real-time data movement.
Develop optimized Spark and SQL workloads with a focus on scalability, reliability, and cost efficiency.
Build and maintain curated datasets and data marts to support analytics, reporting, and AI use cases.
Work with large-scale structured and semi-structured datasets using modern lakehouse architectures.
Collaborate with Product, Engineering, Analytics, and Data Science teams to translate business requirements into robust data solutions.
Ensure data quality through validation frameworks, monitoring, and automated testing.
Troubleshoot production issues, optimize pipeline performance, and continuously improve platform reliability.
Participate in architecture discussions, code reviews, and engineering best practices.
Contribute to reusable frameworks, platform tooling, and technical documentation.

Minimum Qualifications

Bachelor's degree in Computer Science, Information Technology, or a related engineering discipline.
2–4 years of professional experience in Data Engineering, Data Platform Engineering, or a related software engineering role.
Strong proficiency in SQL , including query optimization, window functions, joins, and analytical queries.
Strong programming skills in Python for building production-grade data pipelines and automation.
Hands-on experience with PySpark or Apache Spark for distributed data processing.
Good understanding of Spark fundamentals, including partitions, shuffles, caching, and distributed execution.
Experience designing and maintaining batch and/or streaming data pipelines .
Understanding of ETL/ELT , Change Data Capture (CDC), and incremental data processing.
Familiarity with modern Data Lake/Lakehouse concepts such as the Medallion Architecture (Bronze, Silver, Gold) .
Good understanding of relational databases, data modeling, and database fundamentals.
Familiarity with columnar data formats such as Parquet , Avro , or ORC , and concepts like partitioning and schema evolution.
Strong debugging, analytical, and problem-solving skills.
Experience writing clean, maintainable, and well-tested production code.
Strong communication skills and the ability to collaborate effectively in cross-functional Agile teams.

Preferred Qualifications

Experience with one or more cloud-native data platforms such as Databricks , EMR , Snowflake , BigQuery , or Redshift .
Exposure to distributed query engines such as Trino or Presto .
Experience with streaming technologies such as Kafka , Spark Structured Streaming, or equivalent.
Familiarity with cloud platforms, preferably AWS , including services such as S3, EMR, Glue, Lambda, or IAM.
Exposure to ingestion frameworks such as AWS DMS , Kafka Connect, or similar technologies.
Familiarity with data governance and metadata management platforms such as Unity Catalog .
Experience using BI and self-service analytics tools such as Superset , Tableau, or Power BI.
Understanding of data quality, monitoring, and observability best practices.
Exposure to modern table formats such as Delta Lake , Apache Iceberg , or Apache Hudi .
Databricks or AWS Data Engineering certifications are an added advantage.

What We're Looking For Technical Skills

SQL
Python
PySpark / Apache Spark
ETL / ELT
Data Modeling
Distributed Data Processing
Batch & Streaming Pipelines
Data Lakehouse Concepts

Engineering Practices

Clean Code
Code Reviews
Unit Testing
Production Debugging
Performance Optimization
CI/CD & Git

Soft Skills

Strong ownership and accountability.
Curiosity and passion for learning new technologies.
Excellent analytical and problem-solving skills.
Ability to communicate technical concepts effectively.
Collaborative mindset with a focus on delivering business impact.

Why Join Freight Tiger?

Build a data platform that processes millions of logistics events every day.
Work with modern technologies including Databricks, Spark, Trino, AWS, Delta Lake, and real-time streaming.
Solve complex engineering problems at scale.
Build products that directly power analytics, AI, and decision intelligence for India's largest logistics enterprises.
Learn from a high-performing engineering team with opportunities to grow into Senior Data Engineer and Engineering Leadership roles.

Required Skills

Query optimization Adobe Illustrator Business Intelligence Power BI Python SQL Lakehouse Monitoring ELT Parquet Partitioning Trino AWS Apache CI/CD Git Tableau