SENIOR / LEAD DATA ENGINEER

Bengaluru, Karnataka, India

𝗛𝗶𝗿𝗶𝗻𝗴: 𝗦𝗲𝗻𝗶𝗼𝗿 / 𝗟𝗲𝗮𝗱 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 – 𝗦𝗲𝗿𝘃𝗶𝗰𝗲 𝗟𝗮𝘆𝗲𝗿 / 𝗤𝗧𝗖 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺

𝗖𝗹𝗶𝗲𝗻𝘁: Talpro

𝗟𝗼𝗰𝗮𝘁𝗶𝗼𝗻: Bengaluru, India | Hybrid

𝗝𝗼𝗯 𝗧𝘆𝗽𝗲: Contract

𝗖𝗼𝗻𝘁𝗿𝗮𝗰𝘁 𝗗𝘂𝗿𝗮𝘁𝗶𝗼𝗻: 12 Months

𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲: 8+ Years

𝗕𝘂𝗱𝗴𝗲𝘁: Up to ₹27 LPA

𝗥𝗼𝗹𝗲 𝗢𝘃𝗲𝗿𝘃𝗶𝗲𝘄

Looking for a strong, hands-on, and highly autonomous Senior / Lead Data Engineer to design, build, and operate the Service Layer platform powering enterprise Quote-to-Cash (QTC), customer lifecycle, finance, and enterprise application integrations.

The role requires expertise in distributed systems, event-driven architecture, microservices, data engineering, cloud-native development, and platform reliability. The candidate will also provide technical leadership to a team of engineers, driving solution design, engineering standards, delivery execution, and operational support across multiple integration initiatives.

The platform uses AWS, Kafka / AWS MSK, Go, Python, canonical data models, asynchronous messaging, and cloud-native architecture patterns to process high-volume, business-critical events, with a strong focus on reliability, security, scalability, observability, and operational readiness.

𝗞𝗲𝘆 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀

1. 𝙏𝙚𝙘𝙝𝙣𝙞𝙘𝙖𝙡 𝘿𝙚𝙡𝙞𝙫𝙚𝙧𝙮 & 𝙀𝙣𝙜𝙞𝙣𝙚𝙚𝙧𝙞𝙣𝙜 𝙇𝙚𝙖𝙙𝙚𝙧𝙨𝙝𝙞𝙥

  • Own end-to-end technical delivery, ensuring quality, scalability, security, and operational readiness.
  • Lead and mentor engineers through task planning, technical guidance, code reviews, design reviews, and delivery management.
  • Drive engineering best practices across software development, CI/CD, observability, reliability, security, and cloud-native architecture.
  • Manage multiple concurrent initiatives while balancing business priorities, technical debt, and platform evolution.

2. 𝘼𝙧𝙘𝙝𝙞𝙩𝙚𝙘𝙩𝙪𝙧𝙚 & 𝙋𝙡𝙖𝙩𝙛𝙤𝙧𝙢 𝘿𝙚𝙨𝙞𝙜𝙣

  • Drive architecture decisions for event-driven integrations, canonical data models, orchestration workflows, and platform capabilities.
  • Define engineering standards, secure-by-design principles, cloud best practices, data governance, and non-functional requirements.
  • Design and build Service Layer capabilities covering messaging, orchestration, observability, reconciliation, data migration, operational tooling, and canonical data management.
  • Ensure resilience, scalability, fault tolerance, performance, and supportability.

3. 𝙀𝙫𝙚𝙣𝙩-𝘿𝙧𝙞𝙫𝙚𝙣 𝙄𝙣𝙩𝙚𝙜𝙧𝙖𝙩𝙞𝙤𝙣 & 𝙈𝙞𝙘𝙧𝙤𝙨𝙚𝙧𝙫𝙞𝙘𝙚𝙨

  • Design, develop, and operate real-time event-driven integration services using Go/Golang and Python.
  • Build and enhance the Service Layer platform to orchestrate Quote-to-Cash workflows across enterprise applications.
  • Implement scalable Kafka / AWS MSK event processing, including retries, idempotency, sequencing, message replay, fault recovery, dead-letter queues, and eventual consistency.
  • Build secure, scalable REST APIs, integration services, and enterprise system interfaces.

4. 𝘿𝙖𝙩𝙖 𝙀𝙣𝙜𝙞𝙣𝙚𝙚𝙧𝙞𝙣𝙜, 𝙈𝙞𝙜𝙧𝙖𝙩𝙞𝙤𝙣 & 𝙍𝙚𝙘𝙤𝙣𝙘𝙞𝙡𝙞𝙖𝙩𝙞𝙤𝙣

  • Design and implement large-scale ETL, migration, reconciliation, and data-quality solutions using AWS Glue, Step Functions, Snowflake, PostgreSQL, and ClickHouse.
  • Build and enforce canonical data models, data contracts, transformation layers, and validation frameworks.
  • Standardise communication across multiple enterprise business systems.
  • Ensure data accuracy, traceability, consistency, and operational reliability.

5. 𝘼𝙒𝙎 𝘾𝙡𝙤𝙪𝙙-𝙉𝙖𝙩𝙞𝙫𝙚 𝙀𝙣𝙜𝙞𝙣𝙚𝙚𝙧𝙞𝙣𝙜

  • Design and build cloud-native applications using AWS Lambda, API Gateway, S3, RDS / Aurora PostgreSQL, DynamoDB, SQS, SNS, EventBridge, IAM, CloudWatch, and VPC.
  • Build highly available, business-critical applications with a focus on performance, security, and operational supportability.

6. 𝙆𝙖𝙛𝙠𝙖, 𝘿𝙖𝙩𝙖𝙗𝙖𝙨𝙚𝙨 & 𝘿𝙖𝙩𝙖 𝙋𝙡𝙖𝙩𝙛𝙤𝙧𝙢𝙨

  • Design and operate event-driven and asynchronous systems using Kafka, AWS MSK, RabbitMQ, or equivalent messaging technologies.
  • Apply fault tolerance, retry patterns, idempotency, dead-letter queues, message replay, eventual consistency, sequencing, and event orchestration.
  • Work with PostgreSQL, ClickHouse, relational databases, and DynamoDB / NoSQL databases.
  • Apply data modelling, query optimisation, performance tuning, data validation, and reconciliation frameworks.
  • Work with AWS Glue, Step Functions, Snowflake, and large-scale data workflows.

7. 𝘾𝙄/𝘾𝘿, 𝙎𝙚𝙘𝙪𝙧𝙞𝙩𝙮 & 𝙊𝙗𝙨𝙚𝙧𝙫𝙖𝙗𝙞𝙡𝙞𝙩𝙮

  • Implement CI/CD pipelines, automated testing, code quality, and secure delivery using tools such as GitLab CI, Jenkins, SonarQube, Trivy, and Semgrep.
  • Apply cloud security and secure-by-design principles, including IAM, OAuth2, JWT authentication, encryption at rest and in transit, Secrets Manager, vulnerability management, audit logging, and compliance controls.
  • Design monitoring, alerting, operational dashboards, and end-to-end workflow visibility using CloudWatch, Grafana, Datadog, Prometheus, and OpenTelemetry.
  • Support production operations, incident management, root-cause analysis, troubleshooting, and performance optimisation.
  • Drive metrics-based improvements in reliability, scalability, and platform performance.

8. 𝘾𝙤𝙡𝙡𝙖𝙗𝙤𝙧𝙖𝙩𝙞𝙤𝙣 & 𝙎𝙩𝙖𝙠𝙚𝙝𝙤𝙡𝙙𝙚𝙧 𝙈𝙖𝙣𝙖𝙜𝙚𝙢𝙚𝙣𝙩

  • Partner with Product Managers, Architects, Enterprise Data teams, Engineering, DevOps, and business stakeholders.
  • Define technical roadmaps, execution plans, dependencies, and delivery milestones.
  • Communicate technical risks, trade-offs, design decisions, and mitigation plans clearly.
  • Collaborate across teams to ensure efficient delivery of integration initiatives.

𝗥𝗲𝗾𝘂𝗶𝗿𝗲𝗱 𝗤𝘂𝗮𝗹𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀

  • Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related discipline.
  • 8+ years of software engineering experience.
  • At least 4+ years focused on cloud-native, data engineering, integration, or distributed platforms.
  • 4+ years building cloud-native solutions on AWS.
  • 4+ years working with Go/Golang, Python, AWS services, and Kafka in production environments.
  • Proven experience designing, building, and operating highly available enterprise integration and event-driven platforms.
  • Strong production support, incident management, root-cause analysis, and performance optimisation experience.
  • Proven experience leading and mentoring engineering teams, including task planning, technical guidance, code reviews, and delivery management.
  • Ability to drive architecture decisions for large-scale distributed systems and enterprise integration platforms.
  • Experience managing multiple parallel technical initiatives.
  • Strong hands-on experience in Go/Golang, Python, scalable backend services, event-driven integrations, orchestration workflows, data processing, REST API development, and secure API design.
  • Strong hands-on experience with AWS cloud-native and serverless architecture patterns.

𝗣𝗿𝗲𝗳𝗲𝗿𝗿𝗲𝗱 𝗦𝗸𝗶𝗹𝗹𝘀 & 𝗗𝗼𝗺𝗮𝗶𝗻 𝗘𝘅𝗽𝗼𝘀𝘂𝗿𝗲

  • AWS certifications such as AWS Certified Data Engineer – Associate, AWS Certified Solutions Architect – Associate, AWS Certified Developer – Associate, or equivalent.
  • Experience in Quote-to-Cash (QTC), CRM, ERP, Customer Lifecycle Management, and Enterprise Data.
  • Exposure to large-scale finance, billing, or enterprise integration transformation programmes.
  • Experience building operational dashboards and platform-level reporting for engineering and business teams.

Application Process

Interested candidates who meet the above requirements can share their updated CV at recruitment@spinode.in

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