Cogoport - Senior Data Engineer - ETL (6-10 yrs)

Cogoport is on a mission to bridge the $3.4 trillion Trade Knowledge and Execution Gap, empowering businesses worldwide by simplifying global trade. As a leading Global Trade Platform, we help companies connect with trade partners, optimize logistics, and improve cash flow. Recognized as an Asia-Pacific High-Growth Company (Financial Times) and an Indian Growth Champion (Economic Times),- we are expanding across India, China, Vietnam, Singapore, Thailand, and Indonesia. -

Why Join Us ?

At Cogoport, you'll work with some of the brightest minds in the industry, driving digital transformation in logistics. We foster an entrepreneurial culture, where innovation, impact, and career growth go hand in hand.

- Impact : Work on real-world logistics challenges that directly optimize global trade and supply chain efficiencies.

- Innovation : Develop AI-driven logistics solutions- that improve freight booking, shipment tracking, and cost optimization.

- Collaboration : Work with cross-functional teams- across data science, engineering, and product to deliver impactful solutions.

- Growth : Be part of a fast-growing company and scale next-gen logistics platforms using advanced data engineering and AI.

- Join us in revolutionizing digital freight and logistics!

About the role ?

We are looking for a- Senior Data Engineer (SDE 3) to build scalable, high-performance data solutions- that drive actionable insights for logistics, freight pricing, shipment tracking, and operational efficiencies. -

Key Responsibilities :

1. Scalable Data Pipeline Development :

- Design and develop real-time and batch ETL/ELT pipelines for structured and unstructured logistics data (freight rates, shipping schedules, tracking events, etc.).

- Optimize data ingestion, transformation, and storage for high availability and cost efficiency

- Ensure seamless integration of data from global trade platforms, carrier APIs, and operational databases.

2. Data Architecture & Infrastructure :

- Architect scalable, cloud-native data platforms using AWS (S3, Glue, EMR, Redshift), GCP (BigQuery, Dataflow), or Azure.

- Build and manage data lakes, warehouses, and real-time processing frameworks to support analytics, machine learning, and reporting needs.

- Optimize distributed databases (Snowflake, Redshift, BigQuery, Apache Hive) for logistics analytics -

3. Real-time & Predictive Analytics :

- Develop streaming data solutions using Apache Kafka, Pulsar, or Kinesis to power real-time shipment tracking, anomaly detection, and dynamic pricing.

- Enable AI-driven freight rate predictions, demand forecasting, and shipment delay analytics.

- Improve customer experience by providing real-time visibility into supply chain disruptions and delivery timeline

4. Performance Optimization & Data Governance :

- Ensure high availability, fault tolerance, and data security compliance (GDPR, CCPA) across the platform.

- Improve query performance for large-scale logistics datasets through indexing, partitioning, and caching techniques.

- Implement data quality checks, lineage tracking, and metadata management for transparency and governance.

5. Collaboration & Leadership :

- Work closely with product managers, data scientists, and logistics experts to translate business needs into scalable data solutions. -

- Partner with business teams to deliver revenue-impacting insights on freight, shipments, and trade patterns

Required Qualifications :

- 6+ years of experience- in data engineering, working with large-scale distributed systems.

- Strong proficiency in Python, Java, or Scala- for data processing

- Expertise in SQL and NoSQL databases- (PostgreSQL, Cassandra, Snowflake, Apache Hive, Redshift). -

- Experience with big data processing frameworks- (Apache Spark, Flink, Hadoop).

- Hands-on experience with real-time data streaming- (Kafka, Kinesis, Pulsar) for logistics use cases. -

- Deep knowledge of- AWS/GCP/Azure- cloud data services like S3, Glue, EMR, Databricks, or equivalent. -

- Familiarity with Airflow, Prefect, or Dagster- for workflow orchestration. -

- Strong understanding of logistics and supply chain data- structures, including freight pricing models, carrier APIs, and shipment tracking systems. -

Preferred Qualifications :

- Experience in building predictive analytics solutions for freight rates, demand forecasting, and risk assessment.

- Experience in machine learning model deployment- and MLOps- practices.

- Exposure to real-time analytics and OLAP systems.

- Certifications in AWS/GCP Data Engineering.