Offer summary

Qualifications:

5+ years of experience in data engineering or backend roles with a focus on data processing., Fluent in SQL and strong in programming languages like Java and Scala, with basic Python knowledge., Experience with data pipeline orchestration tools and data warehousing solutions such as Snowflake and Redshift., Good understanding of data privacy and security regulations like GDPR and CCPA..

Key responsabilities:

Develop and maintain data pipelines for internal and in-product analytics.

Collaborate with internal stakeholders to understand client usage of the Workato platform.

Create a usage tracking and billing platform for real-time data integration.

Work closely with the ML team to support current and future data projects.

Job description

About Workato

Workato transforms technology complexity into business opportunity. As the leader in enterprise orchestration, Workato helps businesses globally streamline operations by connecting data, processes, applications, and experiences. Its AI-powered platform enables teams to navigate complex workflows in real-time, driving efficiency and agility.

Trusted by a community of 400,000 global customers, Workato empowers organizations of every size to unlock new value and lead in today’s fast-changing world. Learn how Workato helps businesses of all sizes achieve more at workato.com.

Why join us?

Ultimately, Workato believes in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles. We are driven by innovation and looking for team players who want to actively build our company.

But, we also believe in balancing productivity with self-care. That’s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives.

If this sounds right up your alley, please submit an application. We look forward to getting to know you!

Also, feel free to check out why:

Business Insider named us an “enterprise startup to bet your career on”
Forbes’ Cloud 100 recognized us as one of the top 100 private cloud companies in the world
Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America
Quartz ranked us the #1 best company for remote workers

Responsibilities

As a Senior Data Engineer at Workato, you will be part of the data engineering team that is responsible for maintaining two data circuits.

The first circuit is the raw data layer and pipelines for internal analytics. This helps us understand how our clients use the Workato platform and requires close collaboration with internal stakeholders such as the Product and Business analytics teams.
The second circuit is data, pipelines, and queries for in-product analytics. This helps our users understand how their clients use the products they built using our automation platform.
Your main responsibility will be to develop a new usage tracking/billing platform that will provide accurate near real-time data for both circuits. This platform will also be integrated smoothly with the back office, internal data warehouse, and in-product analytical and reporting tool called Workato Insights. Additionally, the new platform will address advanced use cases like usage forecasting, anomaly detection, and real-time alerts.
You should also be prepared to work closely with the ML team, as the data platform will be an important foundation for current and future projects in this area.
You will work as part of a small, flexible team of 4 engineers and will have a direct impact on modernizing and maturing the platform, including architecture decisions. On a daily basis you will use modern tools such as Iceberg Datalake, Snowflake, Clickhouse, Airflow, Flink, Spark, Trino, and Kafka Ecosystem.

Requirements

Qualifications / Experience / Technical Skills

5+ years of work experience building & maintaining data pipelines on data-heavy environments (Data Engineering, Backend with emphasis on data processing)
Fluent knowledge of SQL.
Strong knowledge of common analytical domain programming languages such as Java, Scala and basic knowledge of Python.
Strong experience with Flink and Spark.
Experience with Data Pipeline Orchestration tools (Airflow, Dagster or similar).
Experience with Data Warehousing Solutions (Snowflake, Redshift, BigQuery).
Production experience with PostgreSQL and Clickhouse is a plus.
Experience with building billing/usage tracking platforms is a plus.
Confidence in using Git, K8s and Terraform.
Experience with a solution cost optimization and capacity planning.
Good understanding of Data Privacy and Security (GDPR, CCPA).

Soft Skills / Personal Characteristics

Good communication and collaboration skills.
Exposure or interest working with Data pipeline technologies.
Readiness to work remotely with teams distributed across the world and timezones.
Spoken English (at the level enough to pass technical interviews and later work with colleagues).

Required profile