To be a technology lead in implementing ETL/DWH solutions with prior experience in the Pharma domain. Should have an overall 6 - 10 years of relevant experience in designing and implementing Data Warehousing, Data Integration and Data lake projects with some experience in pharma or healthcare domain for US based customers.
- Strong proficiency in SQL and NoSQL database design, development and maintenance.
- SQL technologies: SQL Server, Oracle, Redshift and Bigquery
- NoSQL technologies: Cassandara, HBase and Mongo DB
- Proficient in building and optimizing ‘big data’ data pipelines, architectures and datasets using technologies like Spark, Hive, AWS Data Pipeline, Azure Data Factory and Apache Airflow etc
- Proficient in stream-processing systems: Storm, Spark-Streaming, etc.
- Proficient in building processes supporting data transformation, data structures, metadata, dependency and workload management
- Experience in building reusable and metadata driven components for data ingestion, transformation and delivery
- Experience of working closely with Data Science / ML Engineers. Experience of any one DS platform like Knime, Alteryx or Dataiku is desired
- Experience of integrating various systems using Rest APIs or Message Queues is desired
- Experience of using TDD (Test Driven Development) approach with automated unit tests
- Experience of working in large teams and using collobration tools like GIT, Jira and Confluence
- Good understanding of any one cloud platform – AWS, Azure or GCP
- Good understanding of modern architecture patterns like serverless and microservices
- Experience of working in complete Software Development life cycle involving analysis, technical design, development, testing, , trouble shooting, maintenance, documentation and Agile Methodology
- Should have an attitude of willing to learn, accept the challenging environment and confidence in delivering the results within timelines. Should be inclined towards self motivation and self-driven to find solutions for problems.
- Logical Thinking – Able to think analytically, use a systematic and logical approach to analyze data, problems, and situations. Notices discrepancies and inconsistencies in information and materials.
- Task Management – Basic level of task management knowledge and experience. Should be able to plan own tasks, discuss and work on priorities, track and report progress
- Communication – Able to convey ideas and information clearly and accurately to self or others whether in writing or verbal.
- Bachelor’s Degree required / technical undergraduate degree preferred, MBA or equivalent preferred.
- Required Experience:
- Minimum of at least 6 years of relevant experience as Data Engineer
- Behavioral Competency
- Excellent communication skills (must be able to interface with both technical and business leaders in the organization)
- Strong analytical skills to solve and model complex business requirements are a plus