Principal Data Engineer

Title: Principal Data Engineer

Bangalore | India

InCommon is hiring for a US based healthtech company on a mission to provide dignified, high quality care to patients with complex health needs. The company delivers primary, behavioral, and social care through a combination of at-home and virtual care, supported by 24/7 access to dedicated care teams. Powered by technology, evidence-based care models, and strong partnerships across the healthcare ecosystem, the company is focused on improving health outcomes and addressing long standing gaps in care.

About the role:

As a Principal Data Engineer, you will be:

• A mission-critical, early part of our growing team (and company)
• Collaborate across the organization with various teams, including Product, Sales, and Clinical Operations, to rewire health care: Your choices will matter, and you will work across various teams to help execute the choices.
• Drive the change in healthcare: You will build the products to integrate highly fragmented and dispersed healthcare services as an end-to-end experience.
• Be part of building a great engineering culture, maintaining the balance and right tradeoff for building products for speed and tech debt.

Desired skills and experience:

Required:

• 7+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field
• You are entrepreneurial and mission-driven and can present your ideas with clarity and confidence clarity and confidence
• Advanced working SQL knowledge and experience working with relational databases
• Experience building and optimizing ‘big data’ data pipelines, architectures, and data sets. A definite plus with healthcare experience
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
• Strong analytic skills related to working with unstructured datasets
• Build processes supporting data transformation, data structures, metadata, dependency, and workload management
• A successful history of manipulating, processing, and extracting value from large disconnected datasets
• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores
• Strong project management and organizational skills
• Experience supporting and working with cross-functional teams in a dynamic environment

Tech Stack:

• The following is a list of software/tools that would be nice to have, but not required:
• Experience with cloud-based data warehouse: Snowflake
• Experience with relational SQL and NoSQL databases
• Experience with object-oriented/object function scripting languages: Golang, Python, Java, C++, Scala, etc.
• Experience with big data tools: Spark, Kafka, etc.
• Experience with data pipeline and workflow management tools like Airflow

Responsibilities will include:

• Be a data champion and seek to empower others to leverage the data to its full potential
• Understand our complex data ecosystem
• Work with the product team and stakeholders to translate business requirements for data across the company into a technical roadmap and architecture for the platform
• Act as the leading data domain expert and owns platform data architecture
• Lead the technical design and implementation of reliable, scalable, and efficient data infrastructure, data-driven products, and software solutions for external and internal customers
• Provide technical leadership to define overall data engineering best practices, standards, and architectural approaches and drive technical excellence. Identify design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Create and maintain optimal data pipeline architecture with high observability and robust operational characteristics
• Assemble large, complex data sets that meet functional / non-functional business requirements
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL
• Work with stakeholders, including the Executive, Product, Clinical, Data, and Design teams, to assist with data-related technical issues and support their data infrastructure needs.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader