Senior Data Engineer passionate about building robust, scalable data infrastructure and pipelines, working with petabytes of data daily using Databricks, SQL, Python, Airflow, and modern AI development tools.
Locations (2)
Ukraine
Poland
Compensation
Last but not least - valuable compensation for your efforts.
Responsibilities
Design, build, and maintain scalable ETL/ELT pipelines processing petabytes of data
Architect data solutions using modern cloud technologies (AWS, Databricks, Snowflake)
Implement real-time and batch processing workflows using Apache Airflow
Optimize data storage and retrieval patterns for analytical workloads
Implement comprehensive data quality frameworks and monitoring systems
Requirements
Advanced degree in Computer Science, Statistics, Mathematics, or related field
The Principal Software Engineer will lead the development of innovative, scalable software solutions that support complex document review workflows for healthcare payers and providers.
Compensation
Our comprehensive compensation package includes competitive salaries, highly valued health insurance, a 401(k) plan with employer match, paid parental leave, and more.
Responsibilities
Lead the evolution of our document processing pipeline: designing Step Functions state machines, writing the modular Go services that run inside them, and defining contracts that let workflow steps be swapped in and out cleanly.
Own the hard problems around processing real-world PDFs reliably at scale — malformed input, structural variance, and performance across documents from a few pages to tens of thousands.
Build out operational metrics and observability — starting with the document pipeline, extending to other platform areas as needs surface.
Take a concept from "here's roughly the problem" to a shipped, working solution with minimal hand-holding.
Mentor and grow the other engineers working in this space, and advocate for the pipeline's forward progress.
Design, build, and deploy machine learning and generative AI solutions for healthcare, including conversational agents and cloud-native workflows.
Responsibilities
Design, build, and deploy machine learning and generative AI solutions—including conversational agents, natural language processing (NLP/NLU) services, and agentic workflows to solve complex healthcare challenges
Develop, evaluate, and optimize conversational voice and chat bots using platforms such as AWS Bedrock, Bedrock AgentCore, AWS Lex, or related agentic frameworks
Implement and integrate cloud-native AI infrastructure, utilizing AWS services such as Lambda, DynamoDB, S3, API Gateway, IAM, and CloudWatch
Apply enterprise-approved AI tools, Retrieval-Augmented Generation (RAG) patterns, vector databases, and model quantization/optimization techniques to deliver scalable, performant applications
Incorporate Responsible AI practices, guardrails, security controls, and prompt engineering techniques to ensure model accuracy, data privacy, and safe operational deployment
L2 Middleware (primary) storage SRE with hands-on experience in Kafka, AWS services, messaging platforms and production support. The candidate will be responsible for operating, monitoring and troubleshooting middleware, messaging, cloud integration and file transfer services to ensure smooth business operations and service availability.
Locations (2)
Noida, Uttar Pradesh, India
Chennai, Tamil Nadu, India
Responsibilities
Operate and support Apache Kafka / Confluent Kafka environments
Manage and monitor AWS services such as SQS, EventBridge and Lambda
Operate AWS Transfer Family and SFTP-based file exchange services
Monitor end-to-end message and file processing flows
Troubleshoot message failures, queue backlogs, consumer delays and connectivity issues
Senior Cloud & Backend Engineer responsible for improving and scaling a cloud-agnostic AWS platform, developing backend services, and enhancing infrastructure reliability and security.
Responsibilities
Develop, maintain and improve AWS cloud infrastructure using Terraform and IaC
Strengthen and improve existing IaC configurations, infrastructure reliability and platform maturity
Own, maintain and optimise CI/CD pipelines using GitHub Actions and Jenkins
Implement and improve software supply‑chain security processes
Improve AWS monitoring, alerting and operational visibility
Builds and maintains data pipelines and models for Asurion Japan’s AWS data platform, moving it to a next‑generation lakehouse and turning business and BI requirements into analytics‑ready data.
Compensation
Compensation: Will be informed before the 1st interview
Responsibilities
Design, build and operate batch and near‑real‑time data pipelines
Maintain the Airflow, Python and SSIS stack and contribute to the platform migration
Implement data models, medallion layers, marts and aggregates for reporting and analytics
Own pipeline quality, monitoring and alerting; resolve incidents through root‑cause analysis
Write and tune complex SQL; review code, prepare releases, build PoCs and document designs
Requirements
Bachelor's degree or equivalent
Nice to have: Databricks Data Engineer certification
Lead Site Reliability Engineer (SRE) responsible for technical leadership, incident management, automation, observability, and reliability engineering in a hybrid work model.
Responsibilities
Take ownership of technical outcomes and drive engineering excellence
Mentor engineers and provide hands‑on technical guidance
Collaborate with product, platform, operations, and security teams to integrate reliability into the SDLC
Define and track KPIs for reliability, performance, and operational efficiency
Lead production incident management, including detection, triage, escalation, and resolution
Design, develop, and maintain secure data pipelines, transformations, and analytics infrastructure supporting enterprise systems within a Department of Defense (DoD) modernization initiative.
Responsibilities
Design, implement, and maintain data pipelines and ETL processes for AI applications supporting ingestion, transformation, and validation of mission data
Develop and optimize data models and schemas for AI platforms across relational and non-relational databases to support system integrations and analytics
Collaborate with system architects, integration developers, and data analysts to ensure data consistency, security, and integrity across cloud environments
Implement data migration and synchronization between legacy systems, applications, and modern cloud platforms
Utilize AWS services (Glue, Lambda, S3, RDS, Redshift, Kinesis) to build and sustain scalable and fault-tolerant data infrastructure
Requirements
Bachelor’s degree in Computer Science, Information Systems, or a related technical field
Nice to have: AWS Certified Data Engineer – Associate
Nice to have: AWS Certified Developer
Nice to have: CompTIA Security+ CE (DoD 8570)
Nice to have: Certified Data Management Professional (CDMP)
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