Senior Data Engineer
About Gradera
Gradera defines a new category of enterprise transformation called Software-Orchestrated Services™ - where software orchestrates human expertise, digital workers, and enterprise systems to deliver governed outcomes at scale. As an AI Native Services firm, we help enterprises redesign how work gets done across operations, product, engineering, customer experience, data, and enterprise workflows to move beyond fragmented AI pilots and disconnected automation toward measurable business outcomes.
Overview
We are seeking a hands-on, collaborative Senior Data Engineer to drive the technical direction, architecture, and delivery of our data foundation for digital twin and AI-powered enterprise platforms. As Senior Data Engineer, you will be ensuring the delivery of robust, scalable, high-performance data pipelines that power real-time operational intelligence and simulation-ready data products. This role partners closely with data architects, simulation engineers, ML engineers, and platform teams.
Our core data platform stack includes:
Data Platform & Lakehouse
Databricks as the single point of truth for all data
Databricks SQL for analytical queries
Unity Catalog for metadata management and governance
Terradata for data warehouse and business intelligence.
Stream & Event Processing
Apache Kafka for real-time event ingestion and streaming
Structured Streaming for continuous data processing
Delta Live Tables for declarative, quality-enforced pipelines
Specialized Data Stores
TimescaleDB for time-series operational data
Transformation & workflows
Python, Scala, and SQL for data transformation and orchestration
AI/ML workflows on Databricks models
Data Quality & Governance
Great Expectations and Delta Live Tables expectations for data validation
Unity Catalog for metadata management and compliance
Work with Time‑series databases is a plus
Key Responsibilities
Architect and build data foundations that serve digital twin platforms, AI/ML workloads, and operational analytics
Ensure delivery of high-quality, well-governed, and performant data products using Unity Catalog and Delta Lake
Drive adoption of DataOps best practices, including CI/CD for data pipelines, automated testing, and monitoring
Champion data hygiene, quality frameworks, and observability across the data estate
Oversee real-time data ingestion from diverse operational systems and IoT sources
Guide the use of modern data engineering tools, architectural patterns, and emerging technologies
Own the implementation and quality of data lineage, cataloging, and governance to enable trust and compliance
Collaborate with simulation engineers and ML teams to deliver simulation-ready and feature-engineered datasets
Ensure engineering rigor, code quality, and documentation standards are met across the data stack
Facilitate clear communication, knowledge sharing, and effective documentation within the team
Drive development efficiency and alignment with product team priorities through clear prioritization frameworks and delivery metrics.
Preferred Qualifications
5 to 7 years of hands-on data engineering experience
Track record of architecting and delivering scalable, production-grade data platforms
Experience with modern DataOps practices (CI/CD for data, automated testing, pipeline monitoring)
Experience working in cross-functional, agile teams
Highly Desirable
Experience building data foundations for digital twin or simulation platforms
Familiarity with OpenUSD data pipelines or FMI/FMU data integration
Experience with physics-informed or operational ML feature engineering
Track record of delivering data platforms with sub-second latency for real-time operational use cases
Experience thriving in fast-paced, ambiguous environments and balancing rapid delivery with technical excellence
Exposure to industrial domains such as Manufacturing, Logistics, or Transportation is a plus.