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Job Description Summary The Data Engineer will design, build, and optimize scalable, secure data pipelines that power analytics and product platforms. For this role specifically, the focus will be on Machine Learning (ML) and Generative Artificial Intelligence (GenAI) workloads, while contributing to innovation and ensuring compliance with healthcare industry standards. This role is expected to provide strong hands-on technical expertise, collaborate across teams, and contribute to architecture decisions that align engineering practices with organizational goals. Job Description Design, build, and maintain reliable, high-performance data pipelines for large-scale structured and unstructured healthcare data. Use PySpark and modern cloud-based tools (Databricks, AWS Glue, EMR, Snowflake) to transform and process data efficiently. Support ingestion, transformation, and validation processes that ensure data consistency, integrity, and availability. Partner with Data Architects, Data Scientists, and Analysts to translate business needs into scalable engineering solutions. Collaborate with platform and DevOps teams to deploy, scale, and monitor data pipelines using Airflow and Kubernetes. Participate in code reviews, documentation, and continuous improvement efforts across the engineering team. Implement and maintain data validation frameworks to ensure pipeline accuracy and completeness. Contribute to best practices in version control, metadata management, and reproducibility. Stay current with emerging technologies in data engineering and cloud computing, recommending improvements to existing infrastructure. Participate in performance tuning, cost optimization, and scaling strategies for cloud-based data systems. Identify automation opportunities to streamline ETL/ELT processes and reduce operational overhead. Share knowledge and mentor junior team members on tools, techniques, and best practices. Promote a culture of collaboration, innovation, and continuous learning within the engineering organization. Support compliance with SOC 2, HIPAA, and GDPR by adhering to established data privacy and security practices. The Posting Range For This Position Is 100,800.00 - 138,600.00 Education Required Education, Certifications and Experience: Bachelor’s or Master’s degree in Computer Science, Engineering, or related field. Experience 5+ years of experience in data engineering, including building and managing pipelines in cloud-based environments. Knowledge Skills And Abilities Experience with building and operationalizing the data foundations that support machine learning and generative AI use cases, including feature pipelines, training/inference data preparation, and retrieval-ready datasets (e.g., embeddings and vector stores) Familiarity with GenAI skills and adjacent tooling (foundation models, prompt engineering, RAG, embeddings/vector databases, and GenAI orchestration frameworks). Hands-on experience with AWS AI/ML and data services, including Amazon Bedrock, Bedrock Agent Core, SageMaker, Glue, and EMR. Experience designing and optimizing data architectures, including data foundations that support ML and GenAI workloads. Hands-on experience with workflow orchestration (Airflow) and containerization (Kubernetes). Hands-on technical expertise, cross-team collaboration, and contributing to architecture decisions Proficiency in Python, SQL, and distributed data frameworks (PySpark, Databricks, AWS Glue, EMR). Working knowledge of cloud platforms (AWS or Azure) and data warehouses (Snowflake). Familiarity with NoSQL and relational databases, as well as data modeling best practices. Strong analytical, problem-solving, and communication skills. Understanding of compliance frameworks (SOC 2, HIPAA) and secure data management principles. Experience working with healthcare datasets or knowledge of healthcare standards (HIPAA, HL7, FHIR) preferred. The posted salary range is the lowest to highest salary we, in good faith, believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the hiring range and this hiring range may also be modified in the future. A candidate’s position within the hiring range may be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, relevant experience, skills, seniority, performance, shift, travel requirements, and business or organizational needs. This job is also eligible for annual bonus incentive pay. We offer a comprehensive package of benefits including paid time off, 11 holidays, medical/dental/vision insurance, generous 401(k) matching, lifestyle spending account and many other benefits to eligible employees. Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, or any other form of compensation that are allocable to a particular employee remains in the Company's sole discretion unless and until paid and may be modified at the Company’s sole discretion, consistent with the law.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.