Aktana is looking for a talented Lead Data Engineer to help develop and administer large-scale data integration, data processing and data analytics database and platform for Aktana Enterprise SaaS product.
In this role, you will help design, build, and scale our data pipelines, data warehouse, and data lake infrastructure. You will work with technical leadership and help establish development standards and drive Aktana overall technical architecture, engineering practices, and methodologies. You work on our hardest problems, building high quality, architecturally sound systems that are aligned with our business needs.
- Architect, design, and implement large scale data management and business analytics solutions at a detailed level by applying industry knowledge, best practices, and architectural guidance to ensure system functionality, performance, and cost efficiencies
- Architect, design, build, test, implement, and support a metadata-driven ETL data pipeline framework focusing on reusability, scalability, and productivity
- Work with the product, cross-functional teams to gather requirements, build, test, and deploy new data pipelines based on business requirements
- Formulate and implement monitoring, security, and availability policies, procedures and standards relating to server and storage management.
- Manage database updates to production using SQL scripts or other automation technology
- Script and/or develop in-depth application and database monitoring tools and recovery mechanisms.
- Background in tuning and optimizing of MySQL, SQL Server, Oracle, or Postgres environments as well as diagnosing and solving performance issues.
- 7+ years of database development and architecture experience in a production environment supporting large data platforms.
- Expert knowledge in Data warehouse concepts and implementation of Dimensional and star models
- Experience with ETL (required), Python (preferred), Informatica or similar tools
- Programming experience in one or more application or systems languages including Python, Groovy, Java, or Scala
- You have experience building data pipelines (real-time or batch) on large complex datasets
- Working experience with Report designs (preferably Tableau, other tools such as Birst/Cognos/BOBJ/OBIEE are good too), including hands-on experience with complex SQL.
- Working experience with both high volume OLTP and high-volume batch processing
- Tuning experience with high volume OLTP and high-volume batch processing
- Demonstrated understanding of RDBMS clusters and replication with one of RDBMS systems: MySQL, SQL Server, Oracle, or any Columnar database
- Extensive experience on system and database monitoring
- Demonstrated self-motivation and a personal track record of life-long learning
NICE TO HAVE
- Experience in the pharmaceutical and life sciences industry; Familiar with proprietary data including medical / pharmacy claims, prescription data, formulary and sales data, and longitudinal patient-level data
- Experience with cloud big data technologies such as Snowflake, AWS solutions– Glue, EMR, S3, EC2, RDS etc
BS/MS degree in Computer Science or related fields and/or equivalent work experience.
Committed to customer success and innovation, Aktana is at the forefront of transforming how life sciences companies share information with healthcare providers (HCPs). Our proprietary platform harnesses machine learning algorithms to enable marketing and sales teams to seamlessly coordinate and optimize multichannel engagement with HCPs. Today, more than half of the top 20 global pharma companies are using Aktana for intelligent engagement.
Aktana is growing fast and looking for exceptional talent to join our team. We value hard work, transparency, and collaboration – and we like to have fun too! We are Great Place to Work Certified™, an honor given based on validated feedback from employees who report a consistently positive experience working at Aktana.
Headquartered in San Francisco, we also have offices in Philadelphia, London, Barcelona, Tokyo, Osaka, Shanghai, Beijing, Sydney, and Sao Paulo.