<p><p><b>About Us :</b></p><p><br/></p><p>Sense is a diverse, collaborative team tackling one of the most universal challenges in todays workforce.<br/><br/> With a mission to change the way companies engage with talent, were creating a better experience for employers, recruiters, and candidates.<br/><br/> Your work at Sense will impact millions of people around the globe and will be instrumental in evolving an entire industry.<br/><br/> Join us in shaping the workforce of the future! Founded in 2015, Sense is a high-growth HR Tech SaaS startup with offices in the Bay Area and Bangalore.<br/><br/> It has 300+ team members, serves 700+ customers, and has grown 100% year-over-year since launch.
We have raised $90M in funding, backed by GV (Google), SoftBank, Accel, and Avataar Ventures.<br/><br/>As a part of the Sense team, youll play an active role in shaping and developing our products and processes.<br/><br/> Our founders are lifelong entrepreneurs with a history of building, scaling, and successfully exiting large companies.
At Sense, your career goals will be supported through active mentorship and learning and development opportunities.<br/><br/> Were an experienced team and looking for great people to add to our team.<br/><br/><b>Job Description and Responsibilities :</b></p><p><br/>As a Lead Backend Engineer - II on our Core Data & Analytics Team, you will play a critical role in designing and scaling backend systems and data platforms that power analytics, product intelligence, and operational decision-making.</p><br/> You will also help drive the automation of analytics workflows and data-driven applications using AI technologies.<br/><br/><b>System & Platform Architecture :</b><br/><br/>- Architect and manage scalable and reliable data pipelines to support real-time and batch analytics.<br/><br/>- Design and implement systems that enable efficient movement and transformation of large-scale data across databases and warehouses.<br/><br/>- Contribute to the development of backend services and internal platforms that integrate with our data ecosystem.<br/><br/><b>Analytics Automation & AI :</b><br/><br/>- Lead backend initiatives to support the automation of analytics tasks using AI and machine learning frameworks.<br/><br/>- Build infrastructure and services to enable anomaly detection, data quality monitoring, and insight generation at scale.<br/><br/><b>Software Development :</b><br/><br/>- Develop clean, modular, and maintainable backend code, with a strong focus on Python as the primary language.<br/><br/>- Develop database models and optimize performance across relational and analytical stores like MySQL and Snowflake.<br/><br/>- Implement and optimize complex queries strong SQL skills are a must.<br/><br/>- Collaborate with the engineering team to build event-driven systems and APIs to support product and analytics use cases.<br/><br/><b>Infrastructure & Operations :</b><br/><br/>- Utilize cloud platforms (preferably AWS) to deploy and manage backend and data infrastructure.<br/><br/>- Monitor and optimize systems for cost efficiency, scalability, and resilience.<br/><br/><b>Leadership & Collaboration :</b><br/><br/>- Mentor engineers, contribute to hiring and onboarding, and foster a culture of engineering excellence.<br/><br/>- Lead architectural discussions, technical planning, and postmortem reviews.<br/><br/>- Work cross-functionally with analytics, product, infrastructure, and customer-facing teams to align system design with business needs.<br/><br/><b>Expertise and Qualifications :</b><br/><br/>- Bachelors or Masters degree in Computer Science, Engineering, or a related field.<br/><br/>- 8- 14 years of experience in backend or data engineering with proven expertise in designing large-scale systems.<br/><br/>- Strong proficiency in Python and SQL is required.<br/><br/>- Experience working with relational databases and cloud-based data platforms such as MySQL and Snowflake, Databricks, Big Query or any such datawarehouse technologies.<br/><br/>- Familiarity with modern data engineering tools such as Airflow, DBT, AWS DMS, Debezium, Flink, or similar technologies is a strong advantage.<br/><br/>- Strong understanding of distributed systems, data modeling, and data integration patterns.<br/><br/>- Familiarity with event-driven architectures and stream processing is a plus.<br/><br/>- Exposure to AI/ML workflows, data science tools, or analytics automation is a strong advantage.<br/><br/>- Strong leadership, problem-solving, and communication skills.<br/><b><br/></b></p><p><b>Perks & Benefits : </b></p><p><br/></p><p>- Equity<br/><br/>- Medical insurance for employees and dependents<br/><br/>- Quarterly Professional Development allowance<br/><br/>- Company Wellness Days (On months without holidays, you are still given a 3-day weekend)<br/></p><br/></p> (ref:hirist.tech)