Senior Data Engineer

Transflo is a leading provider of mobile, telematics, and business process automation software for the transportation and logistics industry. Our solutions help freight carriers, brokers, and shippers automate and streamline their operations, reduce costs, and improve efficiency. We are on a mission to drive innovation in the industry by providing cutting-edge SaaS and AI solutions that enable seamless communication and collaboration across the supply chain.

DESCRIPTION:

Transflo is seeking a Senior Data Engineer to architect and own our enterprise data platform — from raw ingestion through curated, analytics-ready data products. You will be the foundational engineer behind our data warehouse, data pipeline infrastructure, and the bronze-silver-gold medallion architecture that serves internal analytics teams, operational reporting, and our growing Data as a Service (DaaS) capability.

This role demands both deep technical expertise and a strategic mindset. You will work across a wide range of source systems — APIs, relational databases, No

SQL stores, file-based feeds, and streaming data — normalizing and modeling data into reliable, governed, and high-performance analytical assets. You will build and scale systems designed for near real-time data environments supporting high-traffic, mission-critical workloads in the transportation and logistics industry.

CORE AREAS OF RESPONSIBILITY:

• Architect, build, and evolve a scalable enterprise data warehouse on Amazon Redshift, applying industry-standard concepts including star schemas, snowflake schemas, normalization, denormalization, referential integrity, and performance optimization strategies
• Design and implement bronze, silver, and gold data layer architecture (medallion architecture): raw ingestion, cleansed and standardized intermediate layers, and curated, business-ready data products optimized for analytics consumption
• Develop dimensional data models, fact and dimension tables, slowly changing dimensions (SCDs), and aggregate structures that support BI tooling, ad-hoc analytics, and downstream API consumption
• Apply rigorous data modeling practices including schema design, constraint definition, indexing strategy, sort keys, distribution keys, and query plan optimization within Redshift and connected systems
• Build, own, and maintain robust batch and streaming data pipelines that ingest data from disparate source systems including REST APIs, flat files, IBM DB2, MySQL, Amazon Aurora, Amazon DynamoDB, and PostgreSQL
• Implement real-time and near real-time data streaming architectures using AWS-native services such as Kinesis Data Streams, Kinesis Firehose, MSK (Managed Kafka), and Event Bridge to support low-latency data delivery requirements
• Design pipeline frameworks for data extraction, transformation, and loading (ETL/ELT) using tools such as AWS Glue, dbt, Apache Airflow, or equivalent orchestration platforms
• Ensure pipeline reliability, idempotency, fault tolerance, and automated recovery; build alerting and observability into every data workflow from day one
• Own data quality end-to-end: design and implement automated profiling, cleansing, deduplication, standardization, and validation frameworks that enforce data integrity at each layer of the medallion architecture
• Build and continuously evolve tooling and processes to support data governance including data cataloging, lineage tracking, metadata management, access controls, and data classification
• Define and enforce data contracts between source systems and the warehouse, establishing clear SLAs for freshness, completeness, and accuracy
• Partner with data consumers — Data scientists, Data analytics engineers, BI developers, product managers, and external API clients — to understand consumption patterns and ensure data products meet quality and performance expectations
• Support the architecture and buildout of a reliable, scalable Data as a Service (DaaS) product, enabling external and internal consumers to access curated Transflo data via governed APIs and data sharing mechanisms
• Contribute to the data platform infrastructure using infrastructure-as-code practices (Terraform), ensuring all data…