Job Description
Our Journey So Far
We started as an Engineering, Procurement, and Construction (EPC) company driven by one mission to deliver projects that unite technical excellence, safety, and sustainability through digital intelligence. Over time, we’ve evolved from a traditional contractor into a data-driven innovation hub, connecting design, construction, and operations with cutting-edge technology. Today, our teams manage complex industrial and infrastructure projects. By embedding AI-powered analytics, digital twins, and intelligent contract systems into every phase of the EPC lifecycle, we’re building a smarter, more connected, and more transparent future for engineering.
Why Join Us
We’re entering a new era of engineering where data, AI, and collaboration redefine how projects are designed, managed, and delivered. By combining engineering expertise with digital innovation, we’re creating the next generation of EPC systems from AI-assisted design validation and smart contract analysis to real-time digital twins and project intelligence dashboards. Joining us means helping shape the digital backbone of modern infrastructure, where your ideas directly influence decisions from boardrooms to construction sites, driving safer, smarter, and more sustainable outcomes.
What You’ll Drive Forward
- Design, build, and operate scalable, high-performance data pipelines—both batch and real-time—to support data ingestion, transformation, and analytical workloads.
- Develop and maintain reliable ETL/ELT processes integrating data from a wide range of internal and external sources, including event-driven systems and change data capture (CDC) streams.
- Partner closely with data science, analytics, product, and engineering teams to convert business requirements into robust data solutions that power insights and decision-making.
- Enforce data quality, consistency, traceability, and lineage through strong data governance practices and effective metadata management.
- Continuously monitor, troubleshoot, and optimize data platforms to ensure availability, scalability, performance, and observability.
- Produce comprehensive technical documentation, including pipeline configurations, deployment and setup guides, code documentation, and end-to-end system flow diagrams.
- Contribute to the evolution of data engineering standards, tooling, automation, and best practices across the organization.
- Stay up to date with emerging data technologies and architectural patterns, and evaluate their applicability and value to the platform.
What Powers Your Drive
- 5+ years of hands-on experience in data engineering or large-scale data infrastructure roles.
- Strong experience with big data processing frameworks such as Apache Spark and streaming platforms like Apache Kafka.
- Practical experience with distributed query engines (e.g., Trino) and data transformation frameworks such as dbt or equivalent tools.
- Hands-on experience with modern data lakehouse architectures and table formats, including Apache Iceberg.
- Solid understanding of relational databases (MySQL, PostgreSQL), NoSQL systems (Redis, Elasticsearch), and analytical OLAP engines (StarRocks).
- Experience designing and orchestrating data workflows using tools such as Apache Airflow or n8n.
- Strong background in real-time stream processing technologies (e.g., Spark Structured Streaming, kSQLDB).
- Proficiency in Python and Bash for data processing, automation, and operational tasks.
- Experience with monitoring and observability stacks, including Prometheus, Grafana, and ELK.
- Demonstrated ability to design, optimize, and operate high-throughput data pipelines at scale.
- Strong analytical and problem-solving skills, with a proactive, ownership-driven approach.
- Hands-on experience with Docker for containerized development and deployment.
Join Us
If you’re passionate about building systems that shape the future of engineering, and want your code to power real-world impact we’d love to meet you. Join us and help redefine what’s possible in digital engineering and intelligent EPC delivery.