Senior Data Engineer

We are seeking an experienced Data Engineer with a strong background in data engineering, platform reliability, and technical leadership to support IT business operations. This role will be responsible not only for designing and building data solutions, but also for operating and evolving large-scale, production-grade data platforms that underpin enterprise analytics and decision-making.

You will design, develop, and maintain high-volume, high-availability data pipelines, scalable data models, and enterprise data warehouses. You will be part of a global, high-performing team responsible for delivering data warehouse solutions for enterprise data.

This role requires a strong sense of end-to-end ownership, including data ingestion, processing, performance optimization, platform stability, cost efficiency, and ongoing operational support.

Key Responsibilities

• Design, develop, and maintain robust, scalable data pipelines that ingest, transform, and integrate data from diverse sources, including batch, streaming, APIs, and file-based feeds.
• Own the day-to-day health of data warehouse, including monitoring, alerting, incident triage, root-cause analysis, and continuous reliability improvements.
• Ensure data quality, accuracy, timeliness, and consistency through validation frameworks, automated checks, and clear data contracts.
• Drive performance tuning, scalability improvements, and cost optimization across compute, storage, and query layers.
• Collaborate closely with business stakeholders, IT leaders, product owners, and analysts to define data requirements, KPIs, SLAs, and success metrics.
• Support platform evolution initiatives, including technology upgrades, data migrations, architectural modernization, and onboarding of new data domains.
• Implement and enforce security, access control, compliance, and governance standards across the data ecosystem.
• Evaluate and adopt new tools, technologies, and patterns to improve resilience, maintainability, and developer productivity.
• Document and communicate data architectures, pipelines, operational runbooks, and best practices to enable sustainable platform operations.
• Lead or mentor engineers and contribute to planning, execution, and delivery using Agile methodologies within a DevSecOps operating model.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience, with 6–8+ years of progressive experience in data engineering or platform engineering roles.
• Strong hands-on experience with SQL and Python, with familiarity in additional programming languages and frameworks.
• 3–5+ years of experience building and operating end-to-end data frameworks, including ETL/ELT, orchestration, data pipelines, compute and storage layers, and analytics enablement.
• Proven hands-on expertise with cloud architectures (Azure, AWS, or GCP) and cloud-native data platforms such as Databricks, Synapse, Snowflake, or Redshift.
• Experience with modern data integration patterns, including APIs, streaming, and file-based ingestion, using tools and frameworks such as DBT, SQL, PySpark, and Python.
• Demonstrated ability to run production data platforms, including monitoring, troubleshooting, incident response, performance tuning, and capacity planning.
• Experience working with real-time and unstructured data at scale.
• Strong background in Agile delivery models (Scrum/Kanban) and DevSecOps practices, including CI/CD and infrastructure-as-code concepts.
• Experience leading or mentoring data engineering teams, balancing feature delivery with platform stability and operational excellence.
• Excellent problem-solving, communication, and stakeholder management skills, with the ability to explain complex technical topics to both technical and non-technical audiences.