Top Tech Jobs & Startup Jobs

Develop and maintain automated UI, API, integration, smoke, regression, end-to-end, and performance tests. Build reusable test automation frameworks, mocks, stubs, emulators, and test tools while integrating quality gates into CI/CD pipelines. Review requirements for quality risks, troubleshoot failures, improve testability and coverage, and collaborate with Agile engineering and DevOps teams. Use AI-assisted tools for test development and analysis, contribute to quality metrics, and mentor junior automation engineers.

Support, maintain, troubleshoot, and develop enterprise software products in an Agile environment. Diagnose production issues, perform engineering-level testing, tune SQL performance, document solutions, estimate feature work, assess risks, and collaborate with product managers, product owners, engineering leaders, and stakeholders. The role requires a week of after-hours support availability every three to four months.

Supports, maintains, troubleshoots, tests, and improves PDI enterprise software products. Diagnoses production issues, tunes SQL performance, documents solutions, estimates feature work, and collaborates with product and engineering stakeholders in an Agile environment. Uses AI-assisted development tools and contributes to AI-powered engineering workflows. Provides technical guidance to less experienced engineers and communicates customer risks, status, and escalation needs.

Manages budgeting, forecasting, long-range planning, variance analysis, financial modeling, and management reporting. Partners with business leaders to evaluate performance, risks, opportunities, and strategic initiatives. Develops actionable insights from financial and operational data, supports month- and quarter-end processes, monitors key metrics, and improves FP&A tools and processes.

Analyzes financial and operational data to support planning, forecasting, performance management, and business decisions. Develops dashboards, reports, data models, and automated analytics solutions; validates data quality and reconciles reporting across systems. Partners with Finance and business stakeholders to translate complex questions into actionable insights, recommendations, and process improvements. Applies AI-enabled tools and automation to enhance reporting efficiency, forecasting, and financial analysis.

Leads complex technology sourcing initiatives covering software, SaaS, cloud, and emerging technologies. Develops sourcing and supplier strategies, evaluates markets and vendors, manages RFI/RFP processes, negotiates technology agreements, builds business cases, assesses risk and total cost of ownership, and advises cross-functional stakeholders on technology investments, renewals, supplier performance, and commercial decisions.

Senior data engineer responsible for designing, building, and optimizing scalable cloud-based data pipelines and lakehouse solutions on AWS. Lead complex integrations, implement data modeling and governance, promote engineering best practices, automate infrastructure and CI/CD, mentor engineers, and collaborate with stakeholders to deliver reliable analytics and BI solutions.

Design, build, and maintain AWS-native cloud data pipelines and ETL/ELT processes (S3, Glue, Redshift, AppFlow, Step Functions). Integrate enterprise apps (Salesforce, NetSuite), develop scalable data models, monitor pipeline performance, ensure data quality and governance, support CI/CD and IaC (Terraform), apply AI/ML for data quality/monitoring, and collaborate with stakeholders and peers.

Designs and deploys AI-enabled platform capabilities, integrating LLMs, prompt engineering, RAG, embeddings, and intelligent workflows. Builds AI evaluation and validation frameworks alongside scalable QA automation for APIs, microservices, distributed systems, and platform services. Integrates automated testing into CI/CD pipelines, validates reliability and performance, and collaborates with engineering, product, data, and platform teams. Provides technical leadership on AI engineering, automation, and quality standards.

Develop and maintain PDI software products, participate in application design, troubleshoot and debug issues, perform engineering-level testing, and collaborate with Product Owners and QA Engineers in an Agile environment. The role includes estimating feature work, documenting solutions, assessing project risks, validating requirements, and applying software engineering fundamentals across web stacks and relational databases.