Job Description:

We are seeking a highly skilled Senior Data Engineer to join our growing Data and AI solutions team. This role involves designing and delivering scalable data platforms, building data pipelines, and enabling analytics use cases across cloud environments. The ideal candidate will bring strong experience in data engineering, cloud technologies, and team/project leadership. Experience or interest in Generative AI (Gen AI) is considered a plus, offering opportunities to support AI-driven projects.

Key Responsibilities:

Data Engineering & Platform Development

• Design, implement, and optimize ETL/ELT pipelines for structured and semi-structured data.
• Build and manage data warehouses and data lakehouse architectures (e.g., BigQuery, Snowflake).
• Develop robust data models and transformation logic to support downstream analytics and reporting.
• Implement data governance frameworks, including metadata tagging, access controls, and quality checks.
• Build and maintain data APIs and microservices to support real-time and batch data access.

Technical Leadership & Project Delivery

• Collaborate with project managers and stakeholders to define scope, timelines, and deliverables.
• Ensure high-quality, secure, and reliable implementation across all stages of the data lifecycle.
• Contribute to documentation, testing strategies, and knowledge-sharing within the team.

[Bonus] Gen AI Integration (Optional but Preferred)

• [Bonus] Support development of Gen AI use cases, such as chatbot, semantic search, or document Q&A.
• [Bonus] Familiarity with RAG pipelines, vector databases (e.g., FAISS, Pinecone), and tools like LangChain, LangGraph, or LlamaIndex is advantageous.
• [Bonus] Assist in integrating Gen AI models with enterprise data using Vertex AI, OpenAI, or similar platforms.

Requirements:

Experience:

• 7+ years of hands-on experience in data engineering or backend data platform development.
• 3+ years of experience working on cloud data platforms (preferably GCP, but AWS/Azure acceptable).
• Proven ability to lead data projects and guide technical teams to successful outcomes.

• Technical Skills:
• Big Data & Open Source Expertise: Leverage open-source big data technologies such as Spark, Hadoop, Apache Beam, Kafka, dbt, and Airflow to orchestrate, process, and analyse large datasets efficiently.
• Cloud Data Platforms: Proficient in working with cloud-based data tools and platforms, including GCP BigQuery, Snowflake, Azure Synapse, AWS Redshift, Databricks, Fivetran, Confluent, and MongoDB Atlas.
• Programming Skills: Strong programming abilities in Python, SQL, and NoSQL databases, with a focus on data transformation, processing, and querying.
• API & Microservices Development: Experience in designing and building scalable microservices and data APIs (considered a bonus).
• Generative AI Technologies: Familiarity with Generative AI tools and frameworks, with the ability to integrate them into data solutions (considered a bonus).
• Data Management & Governance: Good knowledge of data management practices and data governance frameworks, including implementing policies, ensuring data quality, and maintaining compliance (considered a bonus).
• Communication & Management Skills:
• Excellent verbal and written communication skills, with the ability to convey complex technical concepts to both technical and non-technical audiences.
• Strong stakeholder management skills to navigate expectations and drive alignment across teams.

• Bonus Skills (Preferred but not required)
• Exposure to Gen AI projects, RAG architecture, or vector databases.
• Experience with LangChain, LangGraph, OpenAI/Gemini APIs, or similar frameworks.
• Familiarity with MLOps, prompt engineering, or fine-tuning LLMs.

Preferred Qualifications:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Certification in cloud platforms such as Google Cloud Professional Data Engineer, AWS Certified Big Data, or Azure Data Engineer Associate.

What We Offer:

• Competitive salary and performance-based incentives.
• Exposure to high-impact projects across data and AI domains.
• A collaborative environment with opportunities to learn and grow in cloud, analytics, and Gen AI technologies.
• Career development support and certification sponsorship.

Please refer to job description.