Senior Backend Engineer - Analytics
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Before you apply
LocationNoida
Work modehybrid
Typefull-time
SenioritySenior
Experience3+ yrs
DepartmentEngineering
Company size51–200 people
PostedAug 20, 2025 · 1y ago
Verified live2d ago
May no longer be actively hiring
Posted by the company on Aug 20, 202549% of this company's open roles have been listed for 90+ days
At a glanceSummarised by Seekless from the posting.
B.E/B.Tech/M.E/M.Tech/PhD from tier 1 Engineering institutes
3+ years of Backend and Infrastructure Experience
Hands-on experience with large-scale databases
Hands-on experience with 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
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
Proficient with platforms such as Snowflake, Amazon Redshift, Google BigQuery, and Azure Synapse Analytics
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
Advanced SQL skills for complex queries, indexing, and performance tuning
Strong in Python or Java for building custom data pipelines and handling advanced data transformations
Experience with real-time data integration tools like Apache Kafka, Apache Spark, AWS Glue, Fivetran, and Stitch
Familiar with workflow automation tools (e.g., Apache Airflow, Luigi) to orchestrate and monitor data pipelines
Knowledgeable in API-based integrations, especially for aggregating data from distributed sources
Experience with Google Cloud
Experience with Django
Experience with Postgres
Experience with Celery
Experience with Redis
Some experience with AI Infrastructure and Operations
Skills
Snowflake
Amazon Redshift
Google BigQuery
Azure Synapse Analytics
Apache NiFi
Apache Airflow
Informatica
Talend
dbt
Python
Java
Apache Kafka
Apache Spark
AWS Glue
Fivetran
Stitch
Luigi
Google Cloud
Django
Postgres
Celery
Redis
About the company
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.
Responsibilities -
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Design and implement analytical platforms that provide insightful dashboards to customers.
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Develop and maintain data warehouse schemas, such as star schemas, fact tables, and dimensions, to support efficient querying and data access.
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Oversee data propagation processes from source databases to warehouse-specific databases/tools, ensuring data accuracy, reliability, and timeliness.
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Ensure the architectural design is extensible and scalable to adapt to future needs.
Requirement -
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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
Nice to have:
•
Experience with Google Cloud, Django, Postgres, Celery, Redis.
•
Some experience with AI Infrastructure and Operations.
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