Jobs at Blackbuck Insights LLC

Develop and customize Salesforce applications using Lightning Web Components, Apex, triggers, data modeling, custom objects, workflows, and formula fields. Integrate Salesforce with internal web applications and third-party platforms such as Amazon Connect and LivePerson. Apply object-oriented design, relational database knowledge, web services, and Agile Scrum methodologies in a collaborative software engineering environment.

Develop and maintain integrations using MuleSoft Anypoint Platform, Mule 4, and DataWeave. Build and manage RESTful and SOAP APIs using RAML and API Gateway, connect cloud platforms such as AWS, Azure, and GCP, and support CI/CD pipelines, Git, and DevOps practices. Apply strong problem-solving and communication skills to deliver reliable integration solutions.

Support healthcare payer integration and member-intelligence initiatives by eliciting and documenting requirements, analyzing payer workflows, mapping data flows, and bridging business and technical teams. Contribute to Member 360, segmentation, testing, defect resolution, cloud and integration delivery, and HIPAA-compliant solutions across eligibility, claims, clinical, pharmacy, provider, care management, and engagement systems.

Architect and govern Azure-based event-driven integration platforms and an AI-powered Snowflake data intelligence platform. Design APIs, routing, transformation, observability, security, semantic layers, RAG memory, inference, recommendation, and agent orchestration systems. Lead architecture workshops, roadmaps, estimates, documentation, stakeholder presentations, and engineering mentorship while ensuring compliance with financial services governance and security requirements.

Develop and maintain responsive Vue.js web applications using JavaScript, Nuxt.js, Vuetify, and reusable components. Build dashboards and data visualizations, integrate REST APIs, modernize legacy applications, and implement routing, state management, authentication, and responsive interfaces from Figma designs. Collaborate on code reviews and feature development while troubleshooting issues and optimizing performance. Use Git-based source control and follow frontend development best practices.

Designs, builds, and optimizes scalable data pipelines, ETL/ELT processes, integrations, and cloud data platforms. Ensures data quality, governance, lineage, observability, reliability, and performance while supporting Meridian initiatives and AI/ML data pipelines. Collaborates with architects, analysts, product owners, and stakeholders; provides technical mentorship; participates in architecture and code reviews; and promotes automation, documentation, testing, and engineering best practices.

Develop and lead scalable machine learning infrastructure, including training, evaluation, deployment, model serving, feature stores, data pipelines, CI/CD, observability, and governance. Collaborate with researchers, data engineers, and product teams to productionize models and support real-time inference. The role includes architectural leadership, code reviews, automation, documentation, and mentoring junior ML engineers.

Designs, develops, and optimizes scalable data pipelines, ETL/ELT processes, integrations, and cloud data platforms. Ensures data quality, governance, reliability, monitoring, and operational efficiency across batch and real-time workflows. Supports Meridian platform implementation, troubleshooting, and deployment while collaborating with architects, analysts, product owners, and stakeholders. Provides technical guidance, participates in architecture and code reviews, mentors engineers, and promotes automation, documentation, and engineering best practices.

Entry-level engineering trainees will contribute across the software and data development lifecycle, including requirements analysis, architecture, coding, testing, deployment, documentation, and maintenance. They will gain hands-on experience with cloud, data engineering, LLMs, prompt engineering, autonomous AI agents, ETL/ELT pipelines, distributed data systems, APIs, CI/CD, and software quality practices. The role requires collaboration, problem-solving, communication, adaptability, and full-time work from the Schaumburg office.

Provides technical leadership for Python software development, including designing scalable server-side applications, defining technology approaches, reviewing code, mentoring engineers, resolving performance issues, and deploying solutions across test and production environments. Collaborates with architects, product owners, business stakeholders, and external teams while contributing to roadmaps, prototypes, documentation, automation, risk mitigation, and continuous development-process improvement.

Develop and maintain Java applications by defining requirements, designing scalable solutions, debugging, reviewing code, implementing security, supporting deployments, and participating in testing. The role requires Java 8+, Spring and Spring Boot, concurrency and asynchronous programming, SQL/PostgreSQL, CI/CD tools, Unix/Linux commands, and unit and integration testing practices.

Leads technical delivery and Agile execution for a wealth management data ingestion platform. Coordinates developers, data analysts, QA data engineers, and DevOps teams; manages sprint planning, backlogs, dependencies, development lifecycle tracking, testing, deployments, risks, and stakeholder communication. The role translates technical requirements into actionable work, aligns enterprise interdependencies, and supports reliable delivery of ETL/ELT pipelines and reporting feeds using Azure DevOps and Microsoft Azure.

Leads data discovery, profiling, quality assessment, and Source-to-Target Mapping for wealth management data platforms. Analyzes complex financial datasets using advanced SQL, documents business rules and transformations, translates requirements for ETL and data engineering teams, supports data governance and testing, and communicates findings to technical and business stakeholders.

Leads data discovery, profiling, quality assessment, and Source-to-Target Mapping for enterprise wealth management platforms. Analyzes client, portfolio, transaction, holdings, performance, and billing data using advanced SQL; documents business rules and transformations; partners with ETL and data pipeline engineers; supports data governance, validation, testing, and stakeholder communication.

Leads end-to-end machine learning research, including problem definition, experimentation, model development, evaluation, and production deployment. Develops advanced models and scalable training pipelines using modern frameworks, collaborates with ML Engineering, MLOps, Product, and Data Engineering, and defines datasets and labeling strategies. Mentors junior researchers, reviews technical work, establishes reproducibility standards, and contributes to AI strategy, roadmap planning, and team development.

Owns finance and accounting operations for US and India entities, including financial close, reporting, FP&A, treasury, cash management, tax and regulatory compliance, audits, internal controls, and process improvement. Manages systems including QuickBooks Online, Tally, Excel, and Power BI while providing financial analysis, forecasts, dashboards, and strategic insights to leadership. Coordinates with internal stakeholders, auditors, tax advisors, banking partners, and external consultants across global operations.

Build and manage data pipelines, ETL workflows, and DAGs using dbt, Apache Airflow, Python, SQL, and Snowflake. Develop custom Airflow operators and hooks, perform data modeling and source-to-target mapping, and implement data quality and cleansing processes. Use cloud platforms, CI/CD, version control, and Snowflake utilities including Snowpipe, Tasks, Streams, stored procedures, and data sharing. Collaborate across teams, communicate insights, solve complex problems, and participate in on-call escalation.