Jobs at DATAECONOMY

Analyze insurance policy, premium, claims, billing, and financial data; build KPI dashboards and reports; write and optimize SQL; validate and model datasets; identify trends, anomalies, fraud indicators, and leakage; and translate business questions into clear recommendations for underwriting, actuarial, claims, finance, and other stakeholders. The role supports pricing, reserving, portfolio management, retention, and loss-ratio analyses.

Design, develop, and maintain scalable backend applications using Core Java, Spring Boot, microservices, REST APIs, and AWS. Responsibilities include optimizing performance, ensuring security and reliability, writing tested code, participating in design reviews, troubleshooting production issues, contributing to CI/CD and DevOps practices, and collaborating with product, architecture, QA, and other teams.

Lead development of scalable web applications using Angular micro frontends and React.js. Responsibilities include designing micro frontend architecture, building reusable components, integrating Angular and React applications, optimizing performance and accessibility, implementing automated tests, troubleshooting complex issues, conducting code reviews, and collaborating with designers, backend engineers, and product managers.

Lead a team building production-grade Generative AI and Agentic AI solutions for banking and financial services. Design RAG pipelines, multi-agent workflows, cloud-native AWS architectures, evaluation and observability frameworks, and reusable GenAI accelerators. Contribute hands-on Python code, guide architecture and code reviews, troubleshoot production issues, document solutions, and ensure security, scalability, compliance, and alignment with BFSI requirements.

Design, develop, and optimize Java-based data applications and microservices. Define scalable technical solutions, drive architecture decisions, mentor engineering teams, and collaborate cross-functionally to deliver reliable, high-performance systems. Use AI productivity tools to improve development efficiency, code quality, and delivery timelines while enforcing coding and performance best practices.

Leads the design and implementation of Neo4j graph database solutions and scalable applications. Responsibilities include graph data modeling, query optimization, performance tuning, data pipeline integration, architecture, security, scalability, stakeholder collaboration, and mentoring. The role translates business needs into technical solutions and guides technical decisions across teams.

Supports Talent Acquisition and HR Operations by sourcing candidates, scheduling interviews, maintaining records, coordinating with stakeholders, updating HR trackers, assisting onboarding, and handling basic employee coordination tasks.

Drive cloud adoption and workload migration within an AWS federated platform environment. Support application teams with AWS landing zones, cloud services, Terraform Enterprise, CI/CD troubleshooting, and DevOps automation. Guide stakeholders, promote Agile and DevOps practices, provide technical enablement, and support cloud transformation initiatives across technical and business teams.

Lead end-to-end delivery of data-centric technical projects, coordinating engineering teams and business stakeholders. Manage planning, timelines, risks, resources, dependencies, and communications using Agile methodologies. Oversee ETL pipelines, data models, integrations, code reviews, and data engineering practices while translating business requirements into technical plans. Collaborate with Product, Data Science, DevOps, and QA teams, provide Python development or debugging support, and track project metrics and stakeholder reports.

Partners with designers, product managers, and engineers to define measurable research questions and guide product decisions. Designs and executes quantitative UX studies using surveys, behavioral data, log analysis, A/B testing, and multivariate testing. Applies statistical models to assess usability and customer satisfaction, builds dashboards and metrics, and translates complex findings into actionable recommendations. Conducts end-to-end primary research addressing user behavior and attitudes while collaborating cross-functionally.

Execute end-to-end SharePoint migrations using ShareGate, including site discovery, readiness assessments, migration waves, cutovers, validation, permissions mapping, troubleshooting, and post-migration support. Manage multiple concurrent migrations, track timelines, risks, and issues, maintain documentation, and communicate with site owners, information stewards, business users, and project leads. Support content cleanup, stakeholder concerns, end-user validation, and escalation of complex migration issues.

Analyze investment and accounting data supporting Asia data modernization and IBOR/ABOR initiatives. Define data requirements, business rules, governance artifacts, and quality checks; perform reconciliations and root-cause analysis; validate Power BI and enterprise reporting datasets; and translate business needs for engineering, BI, product, investment, finance, and risk stakeholders.

Develop, customize, integrate, and support Microsoft Dynamics 365 CRM/CE solutions. Responsibilities include building plugins, workflows, business rules, JavaScript, Power Automate flows, CRM components, integrations, and security models. The role also involves requirements gathering, code reviews, testing, deployments, production support, Agile ceremonies, and technical documentation. Candidates should have strong C# and .NET experience, Power Platform expertise, Azure and CI/CD exposure, SQL Server knowledge, and strong communication and stakeholder-management skills.

Develops executive Tableau dashboards and BI reports for banking, financial services, and insurance stakeholders. Designs governed data models, builds ETL pipelines using Snowflake, writes and optimizes SQL, and manages Tableau Server performance. Ensures dashboard accuracy, security, and visual quality through end-to-end testing. Collaborates with engineers, analysts, and operations teams, facilitates solution workshops, estimates reporting initiatives, and delivers data-driven insights through clear storytelling in Agile environments.

Design and architect scalable Neo4j graph data models and cloud-native data platforms. Build and optimize AWS-integrated data pipelines, APIs, and ingestion patterns; tune Cypher queries, indexes, and execution plans. Establish data governance, lineage, quality standards, schemas, and best practices. Collaborate with product, data science, and engineering teams, make architecture decisions, mentor engineers, and contribute to technical roadmaps and design reviews.

Design and engineer Snowflake solutions using Cortex AI capabilities such as RAG, semantic search, and multi-agent systems. Apply capital markets expertise while communicating with and managing clients. Nice-to-have experience includes PostgreSQL, Talend, Azure or AWS, Denodo, Iceberg tables, and migration from Oracle or DB2 to Snowflake.

Manage strategic software services client relationships, serve as the primary client liaison, identify account expansion opportunities, negotiate contracts and renewals, oversee delivery, resolve escalations, and drive revenue growth. Develop account plans, collaborate with cross-functional teams on upselling and cross-selling, provide market insights, track account performance, and present business reviews. Requires strong software delivery knowledge, communication, negotiation, and stakeholder management skills.

Build and optimize Starburst-based data pipelines and federated queries, integrate databases, data lakes, and warehouses, and ensure performance, reliability, and governance. Collaborate with analytics, AI/ML, and business teams to deliver scalable data platforms and solutions.

Develop and maintain scalable PySpark data pipelines and ETL processes, write optimized SQL for extraction and transformation, manage large structured and unstructured datasets, ensure data quality, resolve performance bottlenecks, and collaborate with cross-functional teams. The role also involves code reviews and applying data engineering best practices. AWS, Airflow, Hadoop, and modern data lake platform experience are preferred.

Design, build, and maintain scalable ETL/ELT pipelines, data platforms, warehouses, lakes, and models. Integrate structured and unstructured data, optimize distributed processing and SQL performance, and ensure data quality, governance, security, lineage, and observability. Lead cloud migrations, modernization, resilience, and incident response initiatives while collaborating with engineering, analytics, data science, risk, compliance, and product teams. Translate business requirements into reliable data solutions and mentor engineers.