Why This Job is Featured on The SaaS Jobs
This Senior Backend Engineer role sits at the intersection of SaaS analytics and AI-enabled customer operations, where product value is often delivered through trustworthy data and clear customer-facing reporting. With Level AI described as a Series C, AI-native platform, the work implied here is less about one-off reporting and more about building durable analytical foundations that can support a maturing SaaS product and its enterprise data expectations.
For a long-term SaaS career, the emphasis on warehouse modeling, ELT orchestration, and real-time integration maps directly to how modern SaaS companies instrument usage, measure outcomes, and operationalize insights. Experience across tools like Snowflake or BigQuery, workflow orchestration, and scalable data propagation translates well to other SaaS environments because the core problems recur: data reliability, performance, extensibility, and making metrics usable inside the product.
This is best suited to an engineer who prefers platform work over feature-only delivery and who enjoys turning messy, distributed data into stable schemas and pipelines. It also fits someone comfortable navigating large codebases and making architectural tradeoffs that keep analytics dependable as product surface area and customer volume expand.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
Level AI was founded in 2019 and is a Series C startup headquartered in Mountain View, California. Level AI revolutionises customer engagement by transforming contact centres into strategic assets. Our AI-native platform leverages advanced technologies such as Large Language Models to extract deep insights from customer interactions. By providing actionable intelligence, Level AI empowers organisations to enhance customer experience and drive growth. Consistently updated with the latest AI innovations, Level AI stands as the most adaptive and forward-thinking solution in the industry.
Competencies:
Data Modelling: Skilled in designing data warehouse schemas (e.g., star and snowflake schemas), with experience in fact and dimension tables, as well as normalization and denormalization techniques.
Data Warehousing & Storage Solutions: Proficient with platforms such as Snowflake, Amazon Redshift, Google BigQuery, and Azure Synapse Analytics.
ETL/ELT Processes: Expertise in ETL/ELT tools (e.g., Apache NiFi, Apache Airflow, Informatica, Talend, dbt) to facilitate data movement from source systems to the data warehouse.
SQL Proficiency: Advanced SQL skills for complex queries, indexing, and performance tuning.
Programming Skills: Strong in Python or Java for building custom data pipelines and handling advanced data transformations.
Data Integration: Experience with real-time data integration tools like Apache Kafka, Apache Spark, AWS Glue, Fivetran, and Stitch.
Data Pipeline Management: Familiar with workflow automation tools (e.g., Apache Airflow, Luigi) to orchestrate and monitor data pipelines.
APIs and Data Feeds: Knowledgeable in API-based integrations, especially for aggregating data from distributed sources.
\n
Responsibilities - - Design and implement analytical platforms that provide insightful dashboards to customers.
- Develop and maintain data warehouse schemas, such as star schemas, fact tables, and dimensions, to support efficient querying and data access.
- Oversee data propagation processes from source databases to warehouse-specific databases/tools, ensuring data accuracy, reliability, and timeliness.
- Ensure the architectural design is extensible and scalable to adapt to future needs.
Requirement -- Qualification: B.E/B.Tech/M.E/M.Tech/PhD from tier 1 Engineering institutes with relevant work experience with a top technology company.
- 3+ years of Backend and Infrastructure Experience with a strong track record in development, architecture and design.
- Hands-on experience with large-scale databases, high-scale messaging systems and real-time Job Queues.
- Experience navigating and understanding large scale systems and complex code-bases, and architectural patterns.
- Proven experience in building high-scale data platforms.
- Strong expertise in data warehouse schema design (star schema, fact tables, dimensions).
- Experience with data movement, transformation, and integration tools for data propagation across systems.
- Ability to evaluate and implement best practices in data architecture for scalable solutions.
Nice to have:
- Experience with Google Cloud, Django, Postgres, Celery, Redis.
- Some experience with AI Infrastructure and Operations.
\n
₹0 - ₹0 a year
\n
To learn more visit : https://thelevel.ai/
Funding : https://www.crunchbase.com/organization/level-ai
LinkedIn : https://www.linkedin.com/company/level-ai/
Our AI platform : https://www.youtube.com/watch?v=g06q2V_kb-s
