Senior Data Engineer – AI & Machine Learning

About the role

TP is looking for a hands‑on Senior Data Engineer – AI to design, build and operate the data foundations that power analytics, automation and AI solutions across client and internal operations.

Key responsibilities

• Architect, build and operate scalable batch and real‑time data pipelines for high‑volume analytics, automation, machine learning and Generative AI workloads.
• Design cloud data lake, lakehouse, warehouse and semantic‑layer architectures aligned with operational and analytical requirements.
• Develop reusable data products, ingestion, transformation and validation components for multi‑client, multi‑country use.
• Prepare trusted, model‑ready datasets for ML, NLP, speech, forecasting and Generative AI use cases.
• Establish data‑quality rules, lineage, metadata, observability and service‑level targets across the data lifecycle.
• Enforce PII protection, client‑data isolation, encryption, role‑based access and regulatory compliance.
• Ensure 24×7 production reliability through monitoring, alerting, incident response and preventive improvements.

Required profile

• 7+ years of data engineering experience, including at least 2 years supporting production AI/ML, NLP or Generative AI workloads.
• Experience delivering enterprise data platforms in high‑volume, multi‑client, regulated or 24×7 environments.
• Strong problem‑solving, architectural thinking and ability to balance business value, risk, scalability and cost.
• Excellent communication with technical, operational, business and client stakeholders.

Required skills

• Advanced SQL and Python.
• ETL/ELT orchestration tools: Airflow, Azure Data Factory, AWS Glue, dbt.
• Distributed processing: Spark, Databricks.
• Cloud data warehouses: Snowflake, BigQuery, Redshift, Synapse.
• Streaming and integration: Kafka, Kinesis, Event Hubs, Pub/Sub, APIs.
• AI data patterns: feature stores, embeddings, vector databases, RAG pipelines.
• Cloud platforms: AWS, Azure, GCP.
• Engineering & governance: Git, CI/CD, containers, Infrastructure as Code.