Job Title: Team Lead – Technology (ETL)
Location: Gurugram, India
ProcDNA is looking for a Team Lead – Technology (ETL) to join our team in Gurguram, India.
Do you want to be a part of commercializing the next generation of life-saving therapies? Do you enjoy working on complex data sets to solve diverse real-world problems and drive business performance? Do you dream of fueling the growth of an early-stage startup? If this describes you, come join us in this exciting journey towards becoming a leader in analytics and technology consulting in the life sciences industry!
ProcDNA is a global consulting firm focused on establishing commercial analytics and technology solutions for life science firms. We work closely with our clients, partnering to achieve their goals. Our people bring a potent blend of design thinking, the latest technology, and a client-centric approach to creating a lasting impact. Since 2021, ProcDNA, which started right at the onset of the pandemic, has had stellar growth. We have grown from 2 to 100+ people and continue with rapid but organic growth. Each of us at ProcDNA (ProcDees) boasts about a healthy mix of learning, new opportunities, and growth, which gives us a feeling of swimming in the open waters rather than confining ourselves to a single lane.
Why considers this role?
If you are working in the healthcare/life-sciences consulting domain but not getting a 360-degree view of the industry this might be a good role for you. At ProcDNA, you will work as a client champion and work across various domains to get a holistic understanding of client needs, you will work directly with senior team members and get an accelerated learning path, which of course will ensure fast-paced personal and professional growth.
What we are looking for:
We are looking for a Team Lead – Technology to join our team. You are someone who has a good understanding of the pharmaceutical industry, has detailed knowledge of various datasets like LAAD, DDD, XPO, etc., enjoys working on complex data sets to help clients solve diverse real-world problems, and drive business performance, navigate risk, and develop pragmatic strategies through data-driven insights.
What you’ll do:
- To collaborate with various teams/regions in driving and facilitating data design, identifying architectural risks and key areas of improvement in the data landscape, and developing and refining data models.
- Technical experience and knowledge in Cloud Data Warehousing, data migration, and transformation- Develop and test ETL components to high data quality and performance standards.
- Hands-on development lead- Familiarity with Data Lakes, Data Warehouses, BI, Dashboards, Design data architecture patterns and ecosystems including data stores (operational systems, data lakes, data warehouses, data marts), ingress patterns (API, streaming, ETL/ELT), and egress patterns (analytics/decision tools, BI tools).
- Experience in leading and delivering data-centric projects with a concentration on Data Quality and adherence to data standards and best practices.
- Experience in data modeling, development, and testing for enterprise-wide data solutions.
- 1.5+ years of relevant experience with Technology.
- Bachelor’s or master’s degree in engineering with strong academic performance.
- Ability to work on and manage multiple concurrent projects for multiple stakeholders with a quality-focused approach.
- Able to understand, identify and recommend reporting needs and improvements.
- Strong verbal, written, and collaboration skills with the ability to articulate results and issues to internal and client teams.
- Proven ability to work creatively and analytically in a problem-solving environment with minimal direction.
- Experience in data modeling, development, and testing for enterprise-wide data solutions- Azure cloud experience is a must-have with the familiarity of the services: Azure Databricks, Azure Data Factory, Azure Data Lake, Spark SQL, PySpark, SQL
- Additional exposure to AWS is good to have.
- Key Skill: Azure Databricks, ADF, ETL, Pipeline Dev, SQL, DWH, ADLS.