Data EngineerExpiring Today!

• Technical Mastery and Execution: At ADG we believe in mastery. We expect you to bring a wealth of experience to the table, specifically in architecting and building robust, scalable batch and real-time streaming pipelines. You must possess a deep understanding of cloud-native data ecosystems, open-source big data specifications, and distributed computing, while also staying at the forefront of GenAI technologies to solve complex, modern problems.
• Project Leadership and Delivery: You will take leading roles in project delivery, ensuring that technical solutions are successfully executed from concept to production. We expect you to drive accountability, manage complex technical timelines, and ensure high-quality outcomes that align with our clients’ strategic goals.
• Business Acumen and Initiative: At ADG, we are always improving. We expect you to go beyond the code to deeply understand the underlying business challenges our customers face and translate complex technical architectures into business value. If you see an opportunity for us to improve our services, architectures, or internal systems, speak up and take the initiative to drive that change.
• Mentorship and Skills Development: We believe in staying certified and ahead of the curve on technologies our customers use and want. This means we expect you to continuously refine your own skills, while also stepping up to mentor junior engineers, guide technical discussions, lead the development of Proof of Concepts (POCs), and elevate the overall capability of our Data practice.

Qualifications & Experience:

• At least 7 years of proven industry experience in data engineering, data architecture, and enterprise software systems.
• A Computer Science (or equivalent) degree, or equivalent practical experience.

Skills & Competencies:

• Deep expertise in modern cloud architectures and GCP data engineering services (e.g., BigQuery, Cloud Dataflow, Cloud Storage, Pub/Sub, Cloud Dataproc, Cloud Composer, and Dataplex) for designing resilient batch and streaming pipelines.
• Exceptional, hands-on proficiency in core Data Engineering technologies, specifically Python, SQL, and Apache Spark, as well as key Data Management concepts.
• Deep understanding of diverse data architectures (e.g., open-source Big Data ecosystems, Hadoop, distributed computing, cloud-native databases, enterprise data lakehouses, and advanced analytics).
• A strong foundational grasp of both traditional data engineering paradigms and modern Generative AI (GenAI) technologies.