Supporting the analytics platform across GCP (BigQuery) and Tableau development. Focus is on data pipeline stability, reporting creation and maintenance, and light migration support from legacy systems (Hive/Presto and Tableau). Work is SLA-based, following defined SOPs from onshore teams.

Key Responsibilities

1. GCP Data Support (BigQuery)

• Create, maintain, and update tables/datasets in BigQuery
• Support migration of tables from Hive/Presto to GCP
• Convert and validate SQL logic (Hive/Presto → BigQuery)
• Ensure data accuracy and consistency post-migration
• Maintain curated datasets for reporting use

1. Tableau Reporting & Migration

• Build and maintain Tableau dashboards on BigQuery datasets
• Support migration of dashboards to a new Tableau instance
• Perform validation and regression testing post-migration
• Ensure dashboard accuracy, refresh stability, and performance

1. Data Ingestion & Stability

• Support automated data ingestion pipelines into GCP
• Monitor scheduled jobs and resolve ingestion failures
• Troubleshoot data issues and coordinate fixes with Data Engineering
• Ensure data availability meets SLA requirements

1. Production Support

• Handle BAU fixes, data updates, and dashboard changes
• Follow SLA timelines for reporting and migration tasks
• Provide status updates and escalate issues as needed

Required Skills

• 2–5 years in BI / data engineering support roles
• Strong SQL (BigQuery + Hive/Presto exposure preferred)
• Experience with GCP (BigQuery)
• Hands-on Tableau dashboard development & maintenance
• Experience with data validation and reconciliation
• Exposure to data migration projects (preferred)

Preferred Skills

• Experience with Freight & Logistics data
• GTM Business exposure
• Python (basic automation)

We are seeking an experienced Principal / Senior Software Engineer, Data & ML Platform to lead the design and development of the foundational data and platform systems that power our AI and machine learning products.

This is a hands-on technical leadership role responsible for architecting scalable, cloud-native infrastructure that enables real-time and batch data services for training, inference, and feedback loops. You will help define the technical direction of our data and ML platform while partnering closely with AI Platform, MLOps, and backend engineering teams.

Key Responsibilities

• Architect and build the core data and software systems that support our AI and ML platforms.
• Design and develop scalable data pipelines, APIs, and platform services for ML and AI use cases.
• Build real-time and batch data frameworks to support model training, inference, and continuous feedback loops.
• Drive platform scalability, reliability, and engineering excellence across distributed systems.
• Partner with cross-functional engineering leaders to shape long-term platform strategy and technical direction.
• Mentor engineers and establish best practices for system design, testing, deployment, and performance optimization.
• Evaluate and implement technologies that improve platform capability, reliability, and developer efficiency.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field; Master’s preferred.
• 7+ years of experience in software engineering, data infrastructure, ML platform, or related engineering roles.
• Strong expertise in Python, Java, and/or PySpark.
• Proven experience designing and scaling cloud-native data and ML systems, preferably in GCP and Databricks.
• Deep understanding of distributed systems, system design, data modeling, and platform architecture.
• Strong experience building and operating large-scale, data-intensive systems.
• Excellent technical leadership, communication, debugging, and problem-solving
• Experience with automated testing, deployment best practices, and production-grade software development.