Lead Software Engineer II Backend Architecture

Job description

<p><p><b>Description :</b></p><br/><p><b>ABOUT US :</b></p><br/><p>Sense is a diverse, collaborative team tackling one of the most universal challenges in todays workforce.

With a mission to change the way companies engage with talent, were creating a better experience for employers, recruiters, and candidates.

Your work at Sense will impact millions of people around the globe and will be instrumental in evolving an entire industry.

Join us in shaping the workforce of the future!</p><br/><p>Founded in 2015, Sense is a high-growth HR Tech SaaS startup with offices in the Bay Area and Bangalore.

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.</p><br/><p>As a part of the Sense team, youll play an active role in shaping and developing our products and processes.

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.

Were an experienced team and looking for great people to add to our team.</p><br/><p><b>JOB DESCRIPTION :</b></p><br/><p>(Not open to contracting or consulting firms)</p><br/><p><b>Roles and Responsibilities :</b></p><br/><p>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.

You will also help drive the automation of analytics workflows and data-driven applications using AI technologies.</p><br/><p><b>System & Platform Architecture :</b></p><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.<p></p><br/><p><b>Analytics Automation & AI :</b></p><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.<p></p><br/><p><b>Software Development :</b></p><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.<p></p><br/><p><b>Infrastructure & Operations :</b></p><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.<p></p><br/><p><b>Leadership & Collaboration :</b></p><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.<p></p><br/><p><b>Expertise and Qualifications :</b></p><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.<p></p><br/><p><br/></p><br/></p> (ref:hirist.tech)

Required Skill Profession

Computer Occupations