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CoffeeBeans

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Senior Data Engineer

Discussion

Summary

Senior Data Engineer at CoffeeBeans (hybrid, Bangalore) owning end-to-end client data engagements from architecture through delivery, building scalable batch and real-time pipelines, data lakes/lakehouses, and warehouses. Core stack: Python, SQL, Databricks, Spark/Flink, Airflow, dbt, and cloud data services.


About the Company


Location: Bangalore


WorkMode: Hybrid


Experience: 7–10 years


Job Type: Full-time


About the Role


We’re looking for seasoned data engineers who can take end-to-end ownership of complex data engineering engagements—right from architecture and design to development and delivery. You’ll work with client stakeholders, lead data initiatives, and guide teams in building modern, scalable data platforms that support business intelligence, advanced analytics, and AI/ML applications.


Responsibilities


  • Lead the design and implementation of scalable, secure, and high-performance data architectures.
  • Architect and optimise data pipelines for batch and real-time processing across varied source systems.
  • Model and implement enterprise-grade data lakes, lakehouses, and warehouses to support analytical workloads.
  • Collaborate with client teams and internal stakeholders to define data strategies, tooling, and standards.
  • Set up and enforce best practices around code quality, pipeline observability, testing, and CI/CD.
  • Guide technical decision-making and mentor junior/mid-level engineers.
  • Troubleshoot complex data issues and provide architectural solutions across heterogeneous systems.


Qualifications


  • Strong expertise in Python and advanced proficiency in SQL.
  • Hands-on experience with Databricks.
  • Deep understanding of data engineering architecture: ETL/ELT pipelines, data modeling (dimensional and normalised), warehousing, streaming systems, and data integration patterns.
  • Proven experience with distributed data processing frameworks (e.g., Apache Spark, Flink).
  • Proficient with orchestration tools like Airflow or similar, and production-grade data workflows.
  • Solid grounding in cloud-native data services (compute, storage, IAM, monitoring).
  • Experience leading technical implementations and collaborating with business stakeholders.


Required Skills


  • Multi-cloud experience (AWS preferred; GCP or Azure familiarity is valued).
  • Hands-on experience with Databricks, dbt, and collaborative data development environments.
  • Awareness of data governance, security, lineage, and quality frameworks.
  • Certifications such as AWS Certified Data Analytics, Databricks Certified Data Engineer Professional, or equivalent.


Preferred Skills


  • Strong leadership, ownership, and client communication skills.
  • Ability to balance hands-on contributions with technical guidance.
  • Adaptability to new tools, tech stacks, and problem domains.
  • Willingness to travel within India for short/medium-term client assignments.


Kindly drop your resume (annesha.manna@coffeebeans.io OR sanchita.s@coffeebeans.io)


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