Svitla Systems Inc. is looking for a Senior Data Engineer for a full-time position (40 hours per week) in India. Our client is a cloud platform for business spend management (BSM) that helps organizations manage their spending, procurement, invoicing, expenses, and supplier relationships. They provide a unified, cloud-based spend management platform that connects hundreds of organizations representing the Americas, EMEA, and APAC with millions of suppliers globally. The platform provides greater visibility into and control over how companies spend money. Small, medium, and large customers have used the platform to bring billions of dollars in cumulative spending under management. The company offers a comprehensive platform that helps organizations manage their spending, procurement, invoicing, expenses, and supplier relationships. Founded in 2006 and headquartered in San Mateo, California, they aim to streamline and optimize business processes, driving efficiency and cost savings.
Requirements
- Experience with processing large workloads and complex code on Spark clusters.
- Experience setting up monitoring for Spark clusters and driving optimization based on insights and findings.
- Understanding designing and implementing scalable data warehouse solutions to support analytical and reporting needs.
- Strong analytic skills related to working with unstructured datasets.
- Understanding of building processes supporting data transformation, data structures, metadata, dependency, and workload management.
- Knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
- Knowledge of Python and Jupyter Notebooks.
- Knowledge of big data tools like Spark, Kafka, etc.
- Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
- Experience with data pipeline and workflow management tools like Azkaban, Luigi, Airflow, etc.
- Experience with AWS cloud services (EC2, EMR, RDS, and Redshift).
- Willingness to work from an office at least 2 times per week.
Nice to have
Knowledge of stream-processing systems (Storm, Spark-Streaming).
Responsibilities
- Optimize Spark clusters for cost, efficiency, and performance by implementing robust monitoring systems to identify bottlenecks using data and metrics. Provide actionable recommendations for continuous improvement.
- Optimize the infrastructure required for extracting, transforming, and loading data from various data sources using SQL and AWS ‘big data’ technologies.
- Work with data and analytics experts to strive for greater cost efficiencies in the data systems.
We offer
- US and EU projects based on advanced technologies.
- Competitive compensation based on skills and experience.
- Annual performance appraisals.
- Remote-friendly culture and no micromanagement.
- Personalized learning program tailored to your interests and skill development.
- Bonuses for article writing, public talks, other activities.
- 15 PTO days, 10 national holidays.
- Free webinars, meetups and conferences organized by Svitla.
- Fun corporate celebrations and activities.
- Awesome team, friendly and supportive community!
About Svitla
Svitla Systems is a global digital solutions company headquartered in California, with business and development offices throughout the US, Latin America, Europe, and Asia. Svitla is an outspoken advocate of workplace flexibility, best known for its well-established remote culture, individual approach to our teammate’s professional and personal growth, and trustworthy environment.
Since 2003, Svitla has served a wide range of clients, from innovative start-ups in California to mega-large corporations such as Ingenico, Amplience, InvoiceASAP and Global Citizen. At Svitla, developers work with clients’ teams directly, building lasting and successful partnerships, as a result of seamless integration with on-site processes.
Svitla Systems’ global mission is to build a business that contributes to the well-being of our partners, personnel and their families, improves our communities, and makes a lasting difference in the world. Join us!
