Integration & Architect

As a Data Engineer, you will be responsible for:

• Delivering data-driven product features by working closely with developers and stakeholders
• Managing backlog items and designing, developing, delivering, and supporting data changes
• Ensuring data structures and database designs meet application, scalability, and architectural standards.
• Building and maintaining ETL pipelines for OLAP and OLTP systems.
• Driving build and release activities for data solutions and supporting related architecture artefacts.
• Continuously improving and optimizing data models and warehouse structures.
• Collaborating with product owners, architects, BAs, and scrum teams to deliver change on schedule., As an Integration Engineer, you will be responsible for:
• Designing, building and owning end-to-end enterprise integrations supporting critical business workflows.
• Developing and maintaining Boomi-based integrations, including process design, connector usage, data mapping, error handling, retries, and environment promotions.
• Building event-driven integrations using Kafka producers and consumers with proper offset management.
• Implementing asynchronous and API-led integration patterns to decouple systems.
• Managing backlog items and delivering integration changes using Agile practices.
• Driving build, deployment, and release activities for integration solutions across environments.
• Ensuring integrations meet scalability, security, auditability, and reliability standards.
• Monitoring and supporting production integrations, including incident analysis, message replay, and recovery.
• Collaborating with product owners, architects, application teams to deliver change on schedule.

• Strong hands-on SQL and Python skills.
• Strong hands-on experience with databases PostgreSQL
• Strong hands-on experience with streaming platform and event-driven architectures
• Strong hands-on experience with AWS cloud services (EKS, EC2, S3, RDS, Lambda, API Gateway, ECS, VPC, IAM, CloudWatch, etc.) and cloud architecture best practices.
• Solid expertise in physical data modelling, DB design, CDC and performance tuning.
• Experience in creating REST API
• Experience designing, developing, and deploying applications using OLTP and OLAP systems.
• Experience with ETL tools such as Boomi; scripting skills in Spark or PySpark are desirable.
• Hands-on experience with CI/CD tools
• Exposure to financial services, compliance, or regulated data domain
• Familiarity with data governance, lineage, and auditability concepts
• Experience working across onsite/offshore teams.
• Strong team player with a willingness to learn new technologies.

Experience

• 10+ years of experience in various databases and ETL tools.
• Must have ETL E2E experience in documentation, development, testing & deployment to Production
• Strong Relational Database background and SQL Skills
• Proficiency in automation and continuous delivery methods
• Proficiency in all aspects of the Software Development Life Cycle in an Agile environment, * Strong hands-on experience with Boomi (process design, connectors, mappings, Atom/Molecule).
• Strong hands-on experience with Kafka including topics, partitions, offsets, and retries.
• Proven experience designing event-driven and message-based architectures.
• Strong understanding of resiliency patterns (idempotency, retries, DLQs, replay).
• Experience building and consuming REST APIs (JSON/XML, authentication, HTTP semantics).
• Ability to troubleshoot and resolve production integration issues, including failed messages or lag
• Familiarity with logging, monitoring, and operational observability.
• Experience working across onsite/offshore teams.
• Strong ownership mindset and willingness to learn evolving integration patterns., * 6+ years of experience in enterprise integration and middleware development.
• Proven end-to-end integration ownership from design through production support.
• Mandatory hands-on experience delivering integrations using Boomi and Kafka.
• Experience supporting business-critical, high-volume integrations in production.
• Strong understanding of integration patterns, data transformation, and error-handling strategies.
• Proficiency in automation, CI/CD, and Agile delivery practices.