Data Engineer

Role Overview

As a senior Data Engineer in ADG’s Data and AI practice, you will design and deliver production-ready data platforms and pipelines for customer engagements and internal needs. You will combine hands-on engineering with technical leadership, helping teams turn business problems into dependable data solutions and exploring how emerging Generative AI approaches can address modern requirements.

Key Responsibilities

• Architect and build scalable batch and streaming pipelines using GCP services and distributed data technologies.
• Guide solutions from discovery and design through implementation, testing, and production deployment.
• Lead delivery on complex projects, coordinating technical work, managing delivery risks, and maintaining quality against customer objectives.
• Apply sound data architecture and management practices across cloud-native platforms, lakehouses, databases, and analytics environments.
• Work with customers to understand their operational and strategic needs, and explain how proposed architectures support measurable business outcomes.
• Assess relevant GenAI frameworks and techniques, developing proofs of concept where they can help solve data or customer challenges.
• Mentor junior engineers, facilitate technical discussions, and share practices that strengthen the wider Data and AI team.
• Identify improvements to ADG’s services, architectures, and internal systems, then take initiative to help put them into practice.

Requirements & Qualifications

• At least 7 years of professional experience in data engineering, data architecture, and enterprise software systems.
• A degree in Computer Science or a related field, or equivalent practical experience.
• Strong practical experience with GCP data services, including BigQuery, Cloud Dataflow, Cloud Storage, Pub/Sub, Cloud Dataproc, Cloud Composer, and Dataplex.
• Advanced hands-on skills in Python, SQL, and Apache Spark.
• Experience designing resilient batch and real-time streaming systems using cloud-native services and distributed computing approaches.
• Broad knowledge of data architectures and management, including open-source big data technologies, Hadoop, cloud-native databases, enterprise lakehouses, and advanced analytics.
• Understanding of established data engineering methods as well as current Generative AI technologies.
• Ability to lead technical delivery, communicate architecture clearly, and support the development of other engineers.

What We Offer / Why Join

• Work across a varied data engineering stack, with a strong focus on GCP, open-source big data technologies, and evolving GenAI frameworks.
• Lead substantial customer projects in a forward-deployed setting, with room to shape technical approaches and contribute directly to customer outcomes.
• A collaborative environment that values autonomy, continued learning, technical mastery, and shared problem-solving.