Total 5 Senior Executive level Information Technology job vacancies in Pune

Job Description

We are looking for you, a Senior Software Engineer to help us build and maintain the next tools or processes that will help the business to overcome our challenges. Help us design, implement and evolve our data analysis tools within a dynamic team working with various technologies.

As a Senior Software Engineer, you will have following key accountabilities:

• Set up, build and maintain WinForms applications (C # / VB.NET) and Office
• Development and maintenance of Backend code on Web tools (C # / ASP.NET)
• Initiate and participate in reflections on the implementation of solutions
• Provide guidance on technology and tooling choices to the team
• Be proactive in the face of various issues
• Respond to the challenges of tool performance
• Participate and support the technological choices of the team (monitoring, mutual aid, presentations, ...)

• Avoid scope-creep, over-engineering, under-testing and technical debt
• Learning our business domain
• Using good software engineering principles and best practices to solve business problems

Essential Duties and Responsibilities

As a Senior Software Engineer, you will play a pivotal role in designing, developing, and delivering high‑quality software solutions while driving engineering excellence across the team. Your key responsibilities include:

• Designing, developing, enhancing, and maintaining backend services and applications using Java, Spring Boot, microservices architecture, and RESTful APIs.
• Collaborating closely with product managers, designers, QA engineers, and cross‑functional teams to gather requirements and deliver scalable, reliable solutions.
• Ensuring code quality, maintainability, and adherence to engineering best practices.
• Conducting comprehensive code reviews and offering constructive technical feedback to peers.
• Debugging, troubleshooting, and resolving complex technical issues in production and non‑production environments.
• Working with DevOps teams to support deployment, orchestration, and monitoring of cloud‑native applications.
• Staying current with emerging technologies, industry trends, and modern engineering practices.
• Mentoring junior team members and contributing to a culture of technical excellence, collaboration, and continuous improvement.

Expectations of the Role

• Availability to work 2 PM – 11 PM IST.

• Work location: Eversana Pune office, with a 5‑day in-person work schedule.

• Strong analytical and problem‑solving mindset.
• Effective communication skills across all levels of the organization.
• Demonstrated commitment to continuous learning and growth.
• Ability to collaborate effectively with internal teams, clients, and external partners.

Qualifications

Minimum Knowledge, Skills, and Abilities

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.

• 6+ years of hands‑on experience as a Software Engineer building enterprise-level applications.

• Strong proficiency in Java and solid understanding of object‑oriented design principles.
• Extensive experience with Spring Boot, Spring Framework, and Spring MVC.
• Proven expertise in microservices architecture and RESTful API development.
• Hands-on experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and containerization tools such as Docker and Kubernetes.
• Knowledge of observability and monitoring tools such as Splunk, AppDynamics, Prometheus, Grafana, or ELK.

• Experience with security best practices, including OAuth2, JWT, and secure coding standards.
• Proficiency with relational databases such as SQL Server, MySQL, PostgreSQL, or Oracle, including query optimization and data modeling.
• Familiarity with Agile methodologies, CI/CD pipelines, and modern DevOps best practices.
• Experience with test automation tools and frameworks (JUnit, Mockito, Selenium, Cypress).
• Strong troubleshooting, debugging, and analytical capabilities.
• Excellent collaborative and communication skills, with experience working in cross-functional environments.
• Hands‑on experience with Incident management processes, including creating, managing, and resolving incidents using ServiceNow or similar ITSM tools.

Additional / Optional Skills (Preferred but Not Mandatory)

• Healthcare domain knowledge, including familiarity with terminology, workflows, regulatory needs (HIPAA, PHI), or experience building healthcare applications.
• Experience with UI/Front‑end development, particularly using React, Angular, or Vue.js.

• Knowledge of JavaScript ES6+, TypeScript, and modern front‑end build tools (Webpack, Vite, npm/yarn).
• Exposure to API Gateways, GraphQL, or gRPC.
• Familiarity with NoSQL databases (MongoDB, Cassandra, DynamoDB).
• Experience working with message‑driven architectures (Kafka, RabbitMQ, AWS SQS/SNS).
• Understanding of distributed systems, performance optimization, and scalability patterns.
• Ability to contribute to architecture discussions and technical design decisions.

SUMMARY:

You’ll join the Xplor Pay Development Team, which provides a full stack payment processing and acquiring platform to integrators, partners, and merchants. Whether small and independent or large franchises, we build services that customers can rely on. You will be involved in the entire software development lifecycle, working with Product Owners, Business Analysts, and others to help deliver and support required functionality across our payment platform, its user interfaces and APIs.

DUTIES AND RESPONSIBILITIES:

• Hands on problem-solving attitude with the ability to generate ideas/solutions and adapt and learn new technologies on the job.
• Write clean, testable, and well-documented code.
• Refactor existing code, write unit tests and review other teammates code.
• Fix problems and defects by collecting information, finding root causes, and implementing solutions.
• Conduct peer reviews for other members of the development team, ensuring that project conventions are adhered to and that requirements are correctly implemented.
• Participate in full-life cycle software development.
• Contribute to performance, diagnostic, and troubleshooting analysis of software.
• Create and maintain documentation for developed APIs.
• Involve and engage with other developers and other teams to motivate and connect with others.
• Mentoring junior team members and guiding them towards raising their own software quality standards.
• Estimate, plan and implement new features in collaboration with product and design.
• Code based on standards and best practices provided by your team lead.
• Keeping up to date with industry trends and technology developments.

Join our DevOps Engineering team as a Senior Database Engineer to design, build, and engineer cloud-native database platforms across a modern, multi-engine data stack. This is an engineering role, not a DBA role, focused on building scalable systems, writing infrastructure-as-code, and embedding databases into software delivery pipelines.

You'll work closely with DevOps and Product Engineering to build high-performing data infrastructure that supports critical applications and analytics.  You will own and evolve a diverse ecosystem spanning AWS RDS, Aurora, DynamoDB, Redshift, Azure SQL, PostgreSQL, Snowflake, and NoSQL engines, integrating AI-driven automation and MLOps-ready data foundations to support critical applications and machine learning workflows.

Key Responsibilities

Multi-Engine Cloud Data Architecture & Platform Engineering

• Design, build, and engineer hybrid data solutions spanning relational (PostgreSQL, Aurora, RDS, Azure SQL), columnar (Redshift, Snowflake), and NoSQL (DynamoDB, DocumentDB, OpenSearch) engines — selecting the right engine per workload.
• Architect cloud-native data lakehouse platforms on AWS using S3, Lake Formation, Glue, and open formats (Apache Iceberg, Delta Lake, Parquet), with Azure Data Lake as a secondary target.
• Implement and manage Medallion Architecture (Bronze / Silver / Gold) patterns to support raw ingestion, curated analytics, and business-ready datasets.
• Build and optimize hybrid data platforms spanning operational databases (PostgreSQL / RDS / Aurora / DynamoDB) and analytical systems (Snowflake / Redshift).
• Develop and maintain semantic layers and analytics models to enable consistent, reusable metrics across BI, analytics, and AI use cases.
• Engineer efficient data models, ETL/ELT pipelines, and query performance tuning for analytical and transactional workloads.
• Engineer replication topologies, partitioning strategies, and data lifecycle automation as code — not manual DBA operations.
• Build automated schema migration pipelines (Flyway/Liquibase) and data versioning workflows integrated into CI/CD replacing manual schema change management.
• Design and implement API-first data access patterns, enabling engineering teams to interact with databases through well-defined, versioned interfaces rather than direct connection strings.

Advanced Data Pipelines, Streaming & Orchestration

• Engineer ELT/ETL pipelines using AWS-native services (Glue, Kinesis, MSK, Step Functions, EventBridge) and modern tooling (dbt, Airflow) for batch, micro-batch, and near-real-time workloads.
• Build streaming data pipelines using AWS Kinesis Data Streams, Kinesis Firehose, and MSK (Managed Kafka) for event-driven, low-latency ingestion across multiple database targets.
• Implement data quality checks, schema enforcement, lineage, and observability across pipelines.
• Optimize performance, cost, and scalability across ingestion, transformation, and consumption layers.
• Implement change data capture (CDC) using AWS DMS, Debezium, or native engine features to synchronize data across SQL, NoSQL, and analytical systems.

NoSQL & Document Store Engineering

• Design and optimize DynamoDB schemas using single-table design patterns, GSIs, LSIs, and DynamoDB Streams for event-driven architectures.
• Architect DocumentDB (MongoDB-compatible) clusters for document workloads requiring flexible schema and hierarchical data models.
• Build and manage OpenSearch / ElasticSearch clusters for full-text search, log analytics, and observability use cases.
• Evaluate and recommend the right NoSQL engine (DynamoDB vs DocumentDB vs OpenSearch vs ElastiCache) based on access patterns, latency, and cost profile.
• Implement TTL policies, DynamoDB Accelerator (DAX), and ElastiCache (Redis/Memcached) for high-throughput caching layers.

AI-Enabled Data Engineering & MLOps Foundations

• Apply AI and ML techniques to data architecture and operations, including intelligent data quality validation, anomaly detection, schema drift detection, and query workload pattern analysis — using AWS SageMaker and Amazon Bedrock.
• Design and build ML-ready data foundations: SageMaker Feature Store, training dataset pipelines, experiment tracking, and inference data pipelines using AWS-native MLOps services.
• Integrate LLM capabilities via Amazon Bedrock for AI-assisted data documentation, query generation, lineage summarization, and automated data cataloging.
• Implement vector database solutions (pgvector on Aurora/RDS, OpenSearch k-NN) to support AI similarity search and retrieval-augmented generation (RAG) use cases.
• Build AI-powered observability using ML-driven anomaly detection on pipeline metrics, query performance trends, and data quality SLAs.

Software Engineering, DevOps & Infrastructure as Code

• Build and manage all data infrastructure as code using Terraform and AWS CDK — covering RDS, Aurora, DynamoDB, Redshift, Glue, MSK, Kinesis, Snowflake, and supporting IAM/networking components.
• Integrate database changes into CI/CD pipelines (GitHub Actions, AWS CodePipeline) with automated schema testing, data contract validation, deployment, and rollback.
• Develop internal platform tooling using Python, SQL, and AWS SDK (boto3) — building self-service capabilities that allow engineers to provision governed database environments on demand.
• Implement database-as-code practices: automated schema migrations, snapshot/restore testing pipelines, and environment clone automation — eliminating manual DBA provisioning tasks.
• Build and publish internal data platform APIs and SDKs that abstract database complexity from application teams.

Security, Governance & Compliance Engineering

• Engineer enterprise-grade data governance across all engines: RBAC, column/row-level security, field-level encryption, dynamic data masking, and comprehensive audit logging, implemented as code, not manual configuration.
• Define and enforce data contracts and ownership using AWS Lake Formation, Glue Data Catalog, and Snowflake governance — versioned and managed in source control.
• Partner with Security and Compliance teams to ensure audit readiness and regulatory alignment (SOC 2, HIPAA, GDPR where applicable).
• Manage AWS IAM policies, KMS encryption, VPC security groups, and private endpoints (PrivateLink, VPC Endpoints) for least-privilege access and network isolation.
• Implement secrets management using AWS Secrets Manager and Parameter Store with automated credential rotation for all database engines.

We are looking for someone to bridge the gap between technical chemical knowledge and enterprise systems/processes, with the following accountabilities and experience.

Accountabilities*

• Manage and validate SAP-EHS data-flows; in co-ordination with Global Hazard Communication functional experts, and IT counterparts as a key member of the internal DevOps Team.
• In collaboration with Global Hazard Communication Experts, bring chemistry and business input into system and process improvement discussions, making recommendations to the function, and identifying opportunities for process automation and efficiency, including for SDS authoring and ERC updates.
• Co-ordinate and manage ERC updates, assessing functional impact, resolving issues, and ensuring alignment with regulatory standards, in co-ordination with Global Hazard Communication Experts.
• Bringing chemistry and data expertise into automation design thinking.
• Act as SAP-EHS data SME in larger change initiatives, involved in UATs and assessing impact.
• Support maintenance of SAP EHS, ensuring data integrity and compliance with regulatory standards.

Experience required for the job

• Minimum 7 years experience with SAP-EHS modules, and with ERC implementation and data verification; ideally with basic understanding of system configuration and customization possibilities.
• Understanding of UN GHS; and CLP, REACH, dangerous goods regulations and regulatory compliance is beneficial.
• Strong experience with data management and EHS systems troubleshooting is a plus.
• Understanding of the SAP EHS data model.
• Understanding of other SAP modules and how they integrate with SAP EHS functionality is a plus.