About Tredence :

Tredence is a global data science and AI-driven company focused on solving the "last-mile" problem in analytics. We help enterprises drive actionable insights by leveraging advanced data engineering, cloud, and AI capabilities across industries.

Role Overview :

We are looking for a hands-on Data Engineer with strong expertise in Google Cloud Platform (GCP) and Scala to join our Data Engineering team. The ideal candidate will design, build, and optimize scalable data pipelines and platforms that enable advanced analytics and AI solutions for global clients.

Key Responsibilities :

- Design, develop, and maintain scalable data pipelines on Google Cloud Platform

- Build and optimize batch and streaming data processing frameworks using Scala

- Develop ETL/ELT workflows using GCP services such as :

1. BigQuery

2. Dataflow (Apache Beam)

3. Pub/Sub

4. Cloud Storage

5. Cloud Composer (Airflow)

- Collaborate with data scientists, analysts, and business stakeholders to support analytics and ML use cases

- Ensure data quality, reliability, and performance across pipelines

- Implement best practices for cloud security, governance, and cost optimization

- Troubleshoot production issues and perform root cause analysis

- Participate in architecture discussions, code reviews, and DevOps processes

Required Skills & Qualifications :

- 6- 12 years of experience in Data Engineering

- Strong hands-on experience with Google Cloud Platform (GCP)

- Proficiency in Scala (mandatory)

- Solid experience with BigQuery and Dataflow / Apache Beam

- Strong understanding of distributed systems, data modeling, and performance tuning

- Experience building ETL/ELT pipelines for large-scale datasets

- Familiarity with SQL, NoSQL, and cloud-based data warehouses

- Knowledge of CI/CD pipelines, version control (Git), and Agile methodologies

- Strong problem-solving and communication skills

Good to Have (Preferred Skills) :

- Experience with Apache Spark / Dataproc

- Exposure to real-time/streaming pipelines using Pub/Sub or Kafka

- Experience with Python alongside Scala

- Understanding of ML data pipelines and feature engineering

- GCP certifications (Professional Data Engineer - preferred)