Senior Data Engineer

SailPoint is the leader in identity security for the cloud enterprise. Our identity security solutions secure and enable thousands of companies worldwide, giving our customers unmatched visibility into the entirety of their digital workforce, ensuring workers have the right access to do their job – no more, no less.

Built on a foundation of AI and ML, our Identity Security Cloud Platform delivers the right level of access to the right identities and resources at the right time—matching the scale, velocity, and changing needs of today’s cloud-oriented, modern enterprise.

About the role:

Want to be on a team that full of results-driven individuals who are constantly seeking to innovate?

Want to make an impact?

At SailPoint, our Data Platform team does just that. SailPoint is seeking a Senior Data/Software Engineer to help build robust data ingestion and processing system to power our data platform. We are looking for well-rounded engineers who are passionate about building and delivering reliable, scalable data pipelines. This is a unique opportunity to build something from scratch but have the backing of an organization that has the muscle to take it to market quickly, with a very satisfied customer base.

Responsibilities:

• Spearhead the design and implementation of ELT processes, especially focused on extracting data from and loading data into various endpoints, including RDBMS, NoSQL databases and data-warehouses.

• Develop and maintain scalable data pipelines for both stream and batch processing leveraging JVM based languages and frameworks.

• Collaborate with cross-functional teams to understand diverse data sources and environment contexts, ensuring seamless integration into our data ecosystem.

• Utilize AWS service-stack wherever possible to implement lean design solutions for data storage, data integration and data streaming problems.

• Develop and maintain workflow orchestration using tools like Apache Airflow.

• Stay abreast of emerging technologies in the data engineering space, proactively incorporating them into our ETL processes.

• Thrive in an environment with ambiguity, demonstrating adaptability and problem-solving skills.

Qualifications:

• BS in computer science or a related field.

• 5+ years of experience in data engineering or related field.

• Demonstrated system-design experience orchestrating ELT processes targeting data

• Must be willing to work 4 overlapping hours with US timezone. will work closely with US based managers and engineers 

• Hands-on experience with at least one streaming or batch processing framework, such as Flink or Spark.

• Hands-on experience with containerization platforms such as Docker and container orchestration tools like Kubernetes.

• Proficiency in AWS service stack.

• Experience with DBT, Kafka, Jenkins and Snowflake.

• Experience leveraging tools such as Kustomize, Helm and Terraform for implementing infrastructure as code.

• Strong interest in staying ahead of new technologies in the data engineering space.

• Comfortable working in ambiguous team-situations, showcasing adaptability and drive in solving novel problems in the data-engineering space.

Preferred 

• Experience with AWS 

• Experience with Continuous Delivery 

• Experience instrumenting code for gathering production performance metrics 

• Experience in working with a Data Catalog tool ( Ex: Atlan / Alation )

What success looks like in the role

Within the first 30 days you will:

• Onboard into your new role, get familiar with our product offering and technology, proactively meet peers and stakeholders, set up your test and development environment.

• Seek to deeply understand business problems or common engineering challenges and propose software architecture designs to solve them elegantly by abstracting useful common patterns.

By 90 days:

• Proactively collaborate on, discuss, debate and refine ideas, problem statements, and software designs with different (sometimes many) stakeholders, architects and members of your team.

• Take a committed approach to prototyping and co-implementing systems alongside less experienced engineers on your team—there’s no room for ivory towers here.

By 6 months:

• Collaborates with Product Management and Engineering Lead to estimate and deliver small to medium complexity features more independently.

• Occasionally serve as a debugging and implementation expert during escalations of systems issues that have evaded the ability of less experienced engineers to solve in a timely manner.

• Share support of critical team systems by participating in calls with customers, learning the characteristics of currently running systems, and participating in improvements.