Lead Data Engineer, IQVIA

• You can make decisions when multiple potential approaches are identified taking into account existing codebase, reduction of operational overhead, team strengths and business priorities
• You are a hands-on, self-directed individual who can bring experience in data engineering to identify incremental or substantial areas of improvement, leading on implementation with best practices
• You will have the ability to mentor and coach data engineering colleagues to support their weekly responsibilities, ongoing professional development, job satisfaction and career potential
• You are a professional who is passionate about improving healthcare and having a real impact having developed yourself as a data engineer with a software engineering background
• You have an appetite to learn and develop yourself, an innate curiosity, and can bring to light clarity around abstract and unclear problems. You feel comfortable working in a self-organizing company
• Extensive experience with Python in a testable and scalable fashion
• History of successfully developing data pipelines (e.g. Prefect, Airflow, Luigi, Dagster)
• Hands on experience with RDBMS (Microsoft SQL or PostgreSQL preferred) and comfortable writing SQL, both DDL and DML
• Experience as lead or managing developer, or substantial experience at senior level
• You are able to clearly explain and translate conceptual ideas and technical rationale to technical and non-technical colleagues
• You have worked as part of teams consisting of 4 or more developers and are used to having your ideas challenged and providing constructive criticism to others
• Ability to autonomously make architecture and design decisions as lead
• Experience with DevOps workflows, especially CI/CD
• Good interpersonal communication and presentation skills
• Attention to detail
• Excellent written and verbal English communication skills

Desirable

• We are seeking a Lead Data Engineer to drive technical direction of data pipeline and data warehouse layers bringing product robustness and maturity during this scale-up period, collaborate with product management to effectively prioritise new features and project needs, and deliver with a team of skilled data engineers
• Lead Design and Development of the data warehouse & ETL pipeline ecosystem, primarily orchestrated within a Prefect-driven architecture utilising Python and SQL
• Deliver data components which differentiate the application within the healthcare and medical research domains, producing robust components deployable in Windows-based and Linux-based environments, implementing new features both large and small, optimising existing functionality
• Design, implement, and improve Python data pipelines with a wide variety of healthcare data sources
• Develop SQL data transformations and connectors for new medical data sources
• Peer review of colleague’s contributions
• Help product owners refine JIRA Epics and User Stories from a technical perspective
• Improve quality through both design decisions and also simply resolving bugs
• Collaborate with other lead developers in Application and AI-Machine Learning teams to integrate other components of the software application such as ElasticSearch and AI / Machine Learning pipelines
• Own design documentation including logical and physical data models, mappings, data flow, data lineage, UML & Entity-Relationship diagrams
• Collaborate with QA to improve test maturity, coverage and automation
• Participate in technical work stream planning with Product and Development teams to clarify requirements, deliverables, monitor/review risks, and provide the necessary engineering expertise & support to ensure delivery
• Line management of data engineering team, owning work intake and prioritisation
• You will be a part of innovation in the medical field, contributing to improved outcomes for healthcare patients and providers
• You will have the opportunity to be responsible for technical communication and preparation in cross-team projects. This will often mean online collaboration with international colleagues
• You will collaborate with Machine Learning specialists gaining exposure to ML and Natural Language Processing (NLP)
• Medical data is an interesting problem space, both in complexity and in societal value. The texts are a domain of its own with extremely high information density. It gives a real kick when users let us know they were able to collect data they were unable to use previously, such as finding people with a rare disease that might take years otherwise to diagnose or rapidly building quality datasets for COVID research
• You will be part of a larger, cross-functional and dynamic team consisting of developers, designers, medical consultants and ML engineers