About the role 

We are seeking an accomplished Senior Data Engineer to join our dynamic and rapidly expanding Tech Ops division. With significant projected growth, this is an opportunity to drive meaningful technical impact. In this role, you will work with internal engineering teams to design, implement, and optimize complex data integration solutions within a modern, large‑scale cloud environment. 

You will leverage advanced skills in distributed computing, data architecture, and cloud-native engineering to enable scalable, resilient, and high‑performance data ingestion and transformation pipelines. As a trusted technical advisor, you will ensure high-quality, compliant data operations across the lifecycle. 

Your day to day 

• Architect, design, and implement high‑volume batch and real‑time data pipelines using PySpark, SparkSQL, Databricks Workflows, and distributed processing frameworks.
• Build end‑to‑end ingestion frameworks integrating Databricks, Snowflake, AWS services (S3, SQS, Lambda), and vendor APIs, ensuring data quality, lineage, and schema evolution.
• Design and optimize data models (star/snowflake schemas) and apply performance tuning techniques for analytical workloads on cloud data warehouses.
• Translate complex business requirements into detailed technical specifications, reusable engineering components, and implementation artifacts.
• Establish and enforce data engineering best practices, including CI/CD for data pipelines, version control, automated testing, orchestration, logging, and observability.
• Drive performance and cost optimization through profiling, cluster tuning, partitioning, indexing, caching, and compute optimization across Databricks and Snowflake.
• Ensure operational excellence and team growth by producing high‑quality documentation (runbooks, architecture diagrams), monitoring and troubleshooting production pipelines, performing root‑cause analysis, and mentoring junior engineers.

What you bring to the team 

• Bachelor’s degree in Computer Science, Computer Engineering, or a closely related technical field, with 5+ years of hands‑on experience as a Data Engineer building and operating large‑scale, distributed data systems in modern cloud environments.
•  Proven ability to clearly communicate complex technical concepts and solutions to both technical and non‑technical stakeholders.
•  Expert‑level proficiency in Python, SQL, and PySpark, including development of distributed transformations and performance‑optimized queries.
• Demonstrated experience designing, building, and operating ETL/ELT pipelines using Databricks, Airflow, or similar orchestration and workflow automation tools.
• Proven experience architecting or operating large‑scale data platforms using DBT, Kafka, Delta Lake, and event‑driven or streaming architectures in cloud‑native data or platform engineering environments.
• Strong working knowledge of AWS data services (S3, SQS, Lambda, Glue, IAM or equivalents), structured and semi‑structured data formats (Parquet, ORC, JSON, Avro), schema evolution, and optimization techniques.
• Hands‑on experience with Terraform and CI/CD pipelines (e.g., GitLab), deep expertise in SQL and compute optimization (partitioning, clustering, Z‑Ordering, pruning, caching), and performance tuning on cloud data warehouses such as Snowflake (preferred), BigQuery, or Redshift

What we would like to see but not required: 

• Working knowledge of U.S. healthcare data domains—including claims, eligibility, and provider datasets—and experience applying this knowledge to complex ingestion and transformation workflows. 

What you’ll get in return 

• Competitive Leave & Benefits
• Comprehensive health coverage
• Equity for every employee – share in our success
• Growth-focused environment – your development matters here

Working Arrangements

• Standard hours: 9 hours/day, 5 working days
• Location: Onsite
• Shift: 10 AM – 7 PM local time

About the role

Our Solution Architecture team is looking to bring on an experienced Solution Architect to support both ongoing and new implementations.  We see significant growth in our future and would love for you to be a part of it! You will partner with customers and numerous internal teams to craft highly scalable, flexible and resilient cloud architectures that provide solutions to solve customer business problems and accelerate the adoption of Abacus’ offerings. As a solutions architect, you will demonstrate best practices around advanced cloud solutions and healthcare payer systems including claims processing (i.e., Medical, Vision, Prescription claims), clinical informatics (e.g., Lab Results), provider systems such as EHR, and CMS Interoperability Mandate solutions.  As a trusted customer advocate, you will have the opportunity to guide a client’s successful adoption of Abacus’ core data management offerings as well as data solutions such as CMS Interoperability, HEDIS and Payment Integrity.

Your day to day

• Collaborate with customers’ business and IT teams to understand the current business and system capabilities and determine the desired state to define the overall technology strategy roadmap
• Author the project architecture design documents, including data flows, sequence diagrams and overall system architecture, that will drive the technical implementation of the solutions.
• Work closely with cross-functional Abacus teams, including business experts, technical business analysts, project managers, sales / account executives and data engineers to successfully implement client projects which reduce technology costs and solution redundancy.
• Collaborate with Product Management to identify client-specific requirements that may translate into an existing standard product feature or a future feature on the Abacus product roadmap.
• Define the solution architecture visions for designated components that describe the long-term goals as well as near-term needs of the client.
• Provide mentorship to internal teams on business needs and use cases for seamless client implementation. Provide ongoing support to address questions and issues raised by the implementation team.

What you bring to the team

• 5 – 7 years of experience in the healthcare IT space, including prior experience in a customer-facing technical role
• Understanding and passion for healthcare data and systems – including payer, provider, and integration partners. Strong working knowledge of US healthcare data, including but not limited to Medical Claims, Pharmacy Claims, Membership / Enrollment, Provider and Clinical.
• Strong communication skills to leverage their domain and technical expertise effectively with the client and build working relationships with internal and external team members. Ability to communicate succinctly and clearly, both verbally and written, across technical and non-technical audiences at multiple levels, including business leaders.
• Working knowledge of GenAI and agentic AI strategies, implementation and governance with a focus on leveraging for efficiency improvements.
• Working knowledge of CMS Interoperability Mandate (9115 / 0057).
• Broad technical knowledge as well as competencies in infrastructure, data models, databases, programming, frameworks, standards, and technical modeling. Strong experience with one or more cloud vendors (AWS / Azure / GCP) and data platforms (Databricks / Snowflake) desired.
• Ability to define the solution architecture vision in architecture design documents
• Experience translating business needs into technology solutions that enable delivery of the Abacus platform.
• Experience working in the payer / healthcare data space and understanding of the historical data architecture needs of our clients.

What we would like to see, but not required:

• Working knowledge of:
  • Provider (EHR) data formats and topics – including FHIR, X-12, HL-7 V2.3, and CCDA/CDA - as well as the general system architecture required to consume and make use of this data.
  • Utilization Management / Care Management / Disease Management business processes / data structures.
  • Medicaid data sets, specifically T-MSIS (Transformed Medicaid Statistical Information System) and how it is used by Medicaid plans.
  • Master Data Management (MDM) processes, tools and strategies.

What you’ll get in return 

• Competitive Leave & Benefits
• Comprehensive health coverage
• Equity for every employee – share in our success
• Growth-focused environment – your development matters here

Working Arrangements

• Standard hours: 9 hours/day, 5 working days
• Location: Onsite
• Shift: 1PM - 10 PM local time