Senior Product Analytics Engineer

Key Skills

Amazon RedShift, Data Analysis, Data Modeling, Data Visualization, Database, Effective communication skills, Google BigQuery, Python Programming, R Programming, Snowflake, SQL

Job Description

About Workato

Workato is the only integration and automation platform that is as simple as it is powerful — and because it’s built to power the largest enterprises, it is quite powerful. 

Simultaneously, it’s a low-code/no-code platform. This empowers any user (dev/non-dev) to painlessly automate workflows across any apps and databases.

We’re proud to be named a leader by both Forrester and Gartner and trusted by 7,000+ of the world's top brands such as Box, Grab, Slack, and more. But what is most exciting is that this is only the beginning. 

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

We are looking for an exceptional Senior Product Analytics Engineer to join our growing team. In this role, you will be responsible for designing and maintaining our analytical infrastructure, analyzing data to extract valuable insights, and providing actionable recommendations to enhance our products. Collaborating with cross-functional teams, you will communicate findings to stakeholders and drive continuous improvement through experimentation. The ideal candidate will have strong technical skills, expertise in data analysis and visualisation, and a passion for working in a dynamic and fast-paced environment. Join our team and play a crucial role in shaping the future of our products through data-driven insights and innovation.

In this role, you will also be responsible to:

• Data Infrastructure and Tools: Design, build and maintain the analytical infrastructure and data pipelines necessary for collecting, processing and analyzing product data. Ensure data quality, integrity, freshness and availability for analysis. Evaluate and implement modern data integration and transformation tools to streamline data workflows.
• Data Governance and Compliance: Ensure compliance with data privacy regulations and adhere to best practices for data governance and security. Maintain data integrity and confidentiality while handling sensitive user and product data.
• Cross-Functional Collaboration: Work closely with cross-functional teams, including product management, data science, and engineering, to gather requirements, define metrics, and align on analytical approaches. Foster collaboration and data-informed discussions to drive consensus and alignment across teams.
• Continuous Improvement: Stay updated with industry trends, emerging technologies, and best practices in product analytics. Proactively identify opportunities to enhance analytical capabilities, introduce new tools or methodologies, and improve data-driven decision-making processes.
• Analyzing Product Data: Utilize data analytics techniques to extract insights from product usage, user behavior and other relevant data, structured and unstructured. Identify trends, patterns and correlations to gain a deep understanding of user needs, product performance, and opportunities for improvement.
• Data-Informed Decision-Making: Collaborate with product managers, engineers, and other stakeholders to provide data-driven recommendations and insights. Influence product strategy, feature prioritization and user experience enhancements based on analytical findings.
• Experimentation and A/B Testing: Plan and execute controlled experiments and A/B tests to evaluate the impact of product changes. Analyze and interpret test results, providing insights and recommendations to optimize product performance and user engagement.

Requirements

Qualifications / Experience / Technical Skills

• Bachelor's Degree in Computer Science, Data Analytics, Information Systems, or a related field, or equivalent work experience.
• 5+ years of relevant experience in the field.
• 2+ years of experience in dimensional and relational data modeling.
• Strong proficiency in data querying languages (SQL), programming languages (Python, R), and data visualization tools..
• Experience with modern data integration and transformation tools such as Fivetran, Dbt, Matillion, Workato, or similar.
• Proficient with cloud databases like Snowflake, Redshift, and BigQuery.
• Strong understanding of database and data warehouse concepts, including facts and dimensions, for designing and developing data models to support enterprise reporting and analytics needs.
• Proven track record of successfully delivering data-driven insights and recommendations to support strategic decision-making.

Soft Skills / Personal Characteristics

• Strong problem-solving and critical-thinking abilities, with a keen attention to detail.
• Experience with agile development methodologies and working in a collaborative team environment.
• Outcome-oriented with strong decision-making skills and the ability to prioritize multiple goals while meeting deadlines.
• Have excellent written and verbal communication skills; exceptional attention to detail.
• Experience working in agile teams using collaboration software like Jira or similar.
• Eager to work in a fast-growing organization with diverse and international teams spread across multiple locations