{"id":2812726,"url":"https://alion.io/job/healthrecon-connect-lead-data-engineer","title":"Lead Data Engineer","company":{"id":4446942,"name":"HealthRecon Connect","domain":"healthreconconnect.com","url":"https://alion.io/company/healthrecon-connect","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Colombo, Sri Lanka"],"countries":["LK"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":16000,"max_usd":37000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":709},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache NiFi","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Embeddings","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Feature Store","optional":false},{"name":"GCP","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"MySQL","optional":false},{"name":"Platform Engineering","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-09-01T12:44:51Z","employer_posted_date":null,"last_verified_at":"2026-09-01T12:44:51Z","board_verified":false,"closed_at":null,"days_open":54,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":54},"description":"HealthRecon Connect provides technology-enabled Revenue Cycle Management solutions to US healthcare providers. The company leverages over 30 years of deep domain expertise, machine learning, AI, cutting-edge analytics, and automated workflows that help improve cash flow, patient outcomes and enable peace of mind for their clients. At HealthRecon Connect, day after day, we not only hold ourselves accountable for setting and maintaining high standards, but we also passionately strive for the highest achievement, customer delight and thrive on the challenge of high expectations and commitment to excel.\n\nHealthRecon was certified a Great Workplace by Great Place to Work® Sri Lanka since 2018 and was adjudged one of the 40 Best Workplaces in Sri Lanka by Great Place to Work® Sri Lanka in 2021. We are also a participant of the United Nations Global Compact.\n\nHRC Labs was established to lead the technological transformation of HealthRecon Connect (HRC). Propelled by the deep domain expertise and industry leading service capability of HRC, HRC Labs focus on enhancing the efficiency of healthcare delivery through intelligent automation solutions for healthcare providers. Our tools sustainably improve clients’ operating margins and cash flows by compressing their working capital cycle and reducing their administrative burden.\n\nWe are currently looking for a Lead Data Engineer to join HRC focused on Revenue Cycle Management (RCM) technology automations and solutions.\n\nDue to the large volume of applications we receive, all applications will be reviewed in the order in which they were received and only the candidates short-listed for the first round of interviews will be contacted. Thank you for your understanding.\n\nJob Vacancy:Lead Data Engineer\n\nWork Week:Monday to Friday\n\nShift Window:03:00 PM – 12:00 AM SLST (Straddle Shift)\n\nImportant: HealthRecon Connect currently operates under a hybrid work arrangement, with the number of remote workdays varying by team. However, depending on client deliverables and business needs, employees may be required to work on-site for all five weekdays.\n\nBy applying, you acknowledge and agree to be available for in-person work five days a week if required.\n\nOther Features:\n\nFull-timeUS calendar applicable\n\nResponsibilities:\n\nOwn and evolve the enterprise data architecture supporting operational, analytical, and AI workloads.\n\nDesign scalable data platforms for transactional databases, analytical data warehouses/lakehouses, and AI/ML data pipelines.\n\nDefine data models, integration standards, metadata management, and data lifecycle strategies.\n\nEstablish best practices for data engineering, architecture, performance optimization, scalability, reliability, and maintainability.\n\nEvaluate and recommend emerging technologies and architectural improvements.\n\nDesign, develop, and optimize robust ETL/ELT pipelines for structured and unstructured data.\n\nBuild reliable batch and real-time data integration pipelines from EHRs, Practice Management Systems, APIs, flat files, and third-party healthcare applications.\n\nDevelop and optimize workflows using tools such as Apache NiFi or equivalent orchestration platforms.\n\nEnsure high data quality, integrity, consistency, lineage, and observability across all data platforms.\n\nSupport relational, NoSQL, and distributed data platforms.\n\nDesign and maintain data platforms supporting Business Intelligence, advanced analytics, and machine learning workloads.\n\nBuild data pipelines that enable AI/ML model training, feature engineering, vector databases, Retrieval-Augmented Generation (RAG), and LLM/SLM applications.\n\nCollaborate with Data Scientists and AI Engineers to operationalize ML models and AI solutions.\n\nSupport MLOps and data versioning best practices.\n\nQualifications/Criteria:\n\nBachelor’s degree in computer science, Software Engineering, or a related field.\n\n10+ years of experience in Data Engineering, Data Platform Engineering, or Data Architecture.\n\nMinimum 5 years of experience working with US Healthcare data, preferably Revenue Cycle Management (RCM), Claims, EHR, or Healthcare Analytics.\n\nEquivalent practical experience with demonstrated technical leadership will also be considered.\n\nProven experience designing enterprise-scale data architecture.\n\nStrong expertise in SQL and data modeling.\n\nHands-on experience with relational databases (PostgreSQL, SQL Server, MySQL, Oracle) and analytical databases/warehouses.\n\nExperience building scalable ETL/ELT pipelines and workflow orchestration.\n\nStrong knowledge of batch and streaming data processing.\n\nExperience with Python for data engineering and automation.\n\nExperience designing cloud-based data platforms (AWS, Azure, or GCP).\n\nWorking knowledge of modern data lake house architectures.\n\nUnderstanding of AI/ML data engineering concepts, including feature stores, vector databases, embeddings, LLMs, and SLMs.\n\nStrong understanding of data governance, metadata management, data quality, security, and access control.\n\nExcellent problem-solving, communication, and stakeholder management skills.","description_format":"text","description_chars":5088,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Hybrid work"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Revenue Cycle & Medical Billing"],"lifecycle":[{"event":"open","at":"2026-10-18T09:02:11Z"}],"visa":[],"liveness":{"score":10,"band":"cold","label":"Long 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