Senior Data Architect

4 weeks ago

Bengaluru, Karnataka, India Data Labs - LANDMARK GROUP Full time
Job Title: Lead Data Engineer

At Data Labs - LANDMARK GROUP, we're seeking a highly skilled Lead Data Engineer to join our team. As a key member of our engineering team, you will be responsible for leading the architecture, design, and delivery of enterprise-grade microservices. Your expertise in data engineering will enable us to build and deploy cutting-edge analytics products for consumption by different stakeholders.

Key Responsibilities:
  • Lead our engineering team in successfully building and deploying analytics products.
  • Design and deliver enterprise-grade microservices.
  • Partner with Product Management, Architects, Operations, and other delivery teams to ensure effective launch and delivery of projects.
  • Help define the Technical Roadmap and own the entire engineering spectrum end-to-end.
  • Improve, optimize, and identify opportunities for efficient data engineering processes.
  • Exhibit strong leadership and communication skills to collaborate with product managers, technology, and management teams across different geographic locations.
  • Drive automated solutions that enable better efficiency and process improvement.
  • Grow and manage the skills and talent in the team.
  • Manage communication cross-functionally and escalate promptly as issues arise.
  • Build and maintain strong working relations with senior internal and external stakeholders.
  • Create a culture that insists on meeting expectations and delivering value.
  • Excellent problem-solving skills.
  • Work with Central IT to ensure integrations of products with downstream and upstream tools.
  • Ensure timely fulfillment of requirements at the platform end to ensure timely delivery of projects.
  • Ensure cost optimization and budget management at Data engineering end by implementing automated alerts, cost dashboards, and proper guardrails for platform utilization by data engineers and business analysts.
  • Timely communication to internal stakeholders on platform events such as downtime, upgrade, etc.
  • Platform stability and maintaining the discussed SLA for services.

Requirements:
  • Bachelor's or master's degree in computer science, Information Systems, or equivalent field.
  • A total of 8+ years of industry experience with 5+ years of experience in architecting and/or developing and delivering end-to-end products/solutions in Analytics domain.
  • Minimum of 4+ years of experience in managing 10-15 Scrum teams.
  • Strong understanding of CS Fundamentals, Data Structures, Algorithms, and Problem Solving.
  • Should be comfortable in working within Microsoft Azure on services like Azure Data Factory, Azure Synapse, Azure DevOps, Azure DataBricks, etc.
  • Experience in microservice architecture, domain-driven design, and RESTful Services.
  • Experience working in a distributed/cloud-based environment (e.g. Azure, Amazon, Rackspace, GCP, etc.).
  • Exposure to continuous integration, unit testing, static analysis, and automated integration tests.
  • Continuous delivery experience preferred.
  • Experience with massive-scale performance and scalability engineering.
  • Very strong understanding and experience in software development lifecycle.
  • 4+ years of experience in a DevOps environment, data integration, and pipeline development.
  • Strong experience in using ETL framework (e.g. Airflow, Oozie, Jenkins, etc.) to build and deploy production-quality ETL pipelines.
  • Experience in ingesting and transforming structured and unstructured data from internal and third-party sources into dimensional models.
  • Strong understanding of distributed storage and compute (Hive and Spark).
  • Experience in building stream processing jobs on Apache Spark or similar streaming analytics technology.
  • Understanding of basics of machine learning would be an added advantage.
  • Understanding software industry trends and relevant innovations in software delivery methods.
  • Ability to continually identify team improvements (retrospective analysis, maturity assessments, and OKRs and KPIs).
  • Strong sense of urgency, learning appetite, and commitment.

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