
Senior Data Engineer
Responsibilities:
● Clean, prepare and optimize data at scale for ingestion and consumption by machine learning models
● Drive the implementation of new data management projects and re-structure of the current data architecture
● Implement complex automated workflows and routines using workflow scheduling tools
● Build continuous integration, test-driven development and production deployment frameworks
● Drive collaborative reviews of design, code, test plans and dataset implementation performed by other data engineers in support of maintaining data engineering standards
● Anticipate, identify and solve issues concerning data management to improve data quality
● Design and build reusable components, frameworks and libraries at scale to support machine learning products
● Design and implement product features in collaboration with business and Technology stakeholders
● Analyze and profile data for the purpose of designing scalable solutions
● Troubleshoot complex data issues and perform root cause analysis to proactively resolve product and operational issues
● Mentor and develop other data engineers in adopting best practices
● Able to influence and communicate effectively, both verbally and written, with team members and business stakeholders
Qualifications:
● 8+ years of experience developing scalable Big Data applications or solutions on distributed platforms
● Experience in Google Cloud Platform (GCP) and good to have other cloud platform tools
● Experience working with Data warehousing tools, including DynamoDB, SQL, and Snowflake
● Experience architecting data products in Streaming, Serverless and Microservices Architecture and platform.
● Experience with Spark (Scala/Python/Java) and Kafka
● Work experience with using Databricks (Data Engineering and Delta Lake components)
● Experience working with Big Data platforms, including Dataproc, Data Bricks etc
● Experience working with distributed technology tools including Spark, Presto, Databricks, Airflow
● Working knowledge of Data warehousing, Data modeling
● Experience working in Agile and Scrum development process
● Bachelor's degree in Computer Science, Information Systems, Business, or other relevant subject area
Role:
Senior Data Engineer
Total No. of Years:
8+ years of relevant experience
To be onboarded by:
Immediate
Notice Period:
Skills
Mandatory / Desirable
Min years (Project Exp)
Max years (Project Exp)
GCP Exposure
Mandatory Min 3 to 7
BigQuery, Dataflow, Dataproc, AI Building Blocks, Looker, Cloud Data Fusion, Dataprep .Spark and PySpark
Mandatory Min 5 to 9
Relational SQL
Mandatory Min 4 to 8
Shell scripting language
Mandatory Min 4 to 8
Python /scala language
Mandatory Min 4 to 8
Airflow/Kubeflow workflow scheduling tool
Mandatory Min 3 to 7
Kubernetes
Desirable 1 to 6
Scala
Mandatory Min 2 to 6
Databricks
Desirable Min 1 to 6
Google Cloud Functions
Mandatory Min 2 to 6
GitHub source control tool
Mandatory Min 4 to 8
Machine Learning
Desirable 1 to 6
Deep Learning
Desirable Min 1to 6
Data structures and algorithms
Mandatory Min 4 to 8

About Kloud9 Technologies
About
Kloud9 was founded with the vision of enabling our customers to transform into an intelligent enterprise with our “AI-First” approach. We help our customers in their data transformation and insights transformation journeys and enable them to make smart business decisions.
At Kloud9, we know AI & ML is one of the key technologies that can help organizations to significantly improve their customer experiences and transform their business operations to enable them to survive & thrive in this global competitive market.
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Location: Bangalore (Hybrid)
Reports to: Co-Founder & CBO
About the Role
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- Collaborate closely with internal teams (design, engineering, research) and client stakeholders to translate project objectives into actionable plans with clear timelines, milestones, and deliverables.
- Define and manage project scope, resourcing, dependencies, budgets, and risks — proactively identifying and mitigating potential blockers.
- Bring clarity and structure to execution by setting up robust documentation, operating rhythms, and tracking mechanisms; ensure timely communication of progress, challenges, and escalations to leadership and clients.
- Drive project governance through weekly health reviews, accurate status reports, and rigorous issue/risk tracking with defined accountability.
- Own the quality of delivery — ensure alignment of deliverables with project goals, client expectations, and internal benchmarks for innovation and excellence.
- Make data work for you — use structured data and reporting to surface insights, enable decision-making, and identify areas of improvement.
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- Embrace a problem-solving mindset — proactively drive solutions to cross-functional execution challenges, and be comfortable navigating trade-offs.
- Contribute to internal IP and process improvements that enhance delivery maturity and scalability across projects.
Requirements
- 5–8 years of experience in project management, with a proven track record of driving end-to-end execution of complex digital or technology projects.
- Prior experience in a service-based or consulting environment, managing external client stakeholders and internal cross-functional teams.
- Strong understanding of digital product development lifecycle — from strategy to design to engineering execution.
- Demonstrated ability to manage project scope, budgets, timelines, and risks with a high sense of ownership and accountability.
- Proficiency in project management tools such as Jira, Asana, Trello, or ClickUp; comfort with setting up and customizing workflows, reports, and dashboards.
- Strong analytical mindset — ability to work with data, identify trends, generate insights, and support decision-making through structured reporting.
- Excellent written and verbal communication skills — capable of simplifying complex ideas, aligning diverse stakeholders, and presenting with clarity to clients and leadership.
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Good to have:
- Experience in managing digital transformation, innovation-led, or customer experience focused projects.
- Exposure to product strategy, UX research, or agile software development practices.
- Certification in PMP, PRINCE2, or Agile methodologies is a plus, but not mandatory.
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