Senior Data Engineer

Neuiq Technologies; Mumbai; Hybrid; INR 1,500,000 - 2,100,000; Full time

Job summary

Neuiq Technologies in Mumbai is seeking an experienced Data Engineer to design, build, and manage scalable data pipelines and data warehousing solutions. You will develop APIs and integrate SaaS data sources to support growing data volumes and complex analytics.

The role requires 3–7 years of hands-on experience with Python, SQL/NoSQL, PySpark, and modern ETL tools. You will collaborate with AI/ML, BI, and product teams to enable high-quality datasets and robust data governance.

Qualifications

• 3–7 years of data engineering experience.
• Strong Python and SQL skills with experience in data pipelines.
• Experience with cloud data warehouses and ETL tooling.

Responsibilities

• Design and implement ETL processes for data transformation and preparation.
• Architect and manage data warehousing solutions.
• Build and maintain data pipelines for analytics and operations.
• Implement and manage CI/CD pipelines for data engineering.
• Oversee data governance to ensure data quality and consistency across sources.
• Ensure data accuracy and integrity across multiple sources and systems.
• Collaborate with AI/ML, BI, and product teams to define data needs.
• Develop and manage data models, schemas, and transformations for analytics.
• Optimize performance of queries, pipelines, and data stores for scalability and cost efficiency.
• Ensure data quality, validation, and lineage tracking using QA or automated checks.
• Lead data migration projects with minimal disruption.
• Stay up-to-date with latest DATA/AI technologies and tools.

Skills

Python

Linux shell

SQL/NoSQL

PySpark

Airflow

dbt

Databricks

Redshift

BigQuery

Snowflake

Kafka

Data governance

Education

B.Tech/B.E. in CS/IT or related field

Tools

Databricks

AWS Redshift

Google BigQuery

Snowflake

Airflow

dbt

Job description

Role overview:

Responsible for designing, building, and managing the infrastructure and tools that allow for the efficient processing and analysis of large data sets. Need to develop and maintain scalable data pipelines and build out new API integrations to support continuing increases in data volume and complexities.

Experience:

3-7 years of experience

Key Responsibilities:

• Design and implement ETL processes for data transformation and preparation
• Architect and manage data warehousing solutions.
• Build and maintain data pipelines for analytics and operational use.
• Implement and manage CI/CD pipelines for data engineering processes.
• Oversee data governance initiatives to ensure data quality and consistency across various sources1.
• Ensure data accuracy and integrity across multiple sources and systems
• Collaborate with the AI/ML, BI, and Product teams to define data needs and ensure availability of high-quality datasets.
• Develop and manage data models, schemas, and transformations for analytics use cases.
• Optimize performance of queries, pipelines, and data stores for scalability and cost efficiency.
• Ensure data quality, validation, and lineage tracking using QA or automated checks.
• Lead data migration projects, ensuring minimal disruption and data integrity.
• Stay up-to-date with the latest advancements in DATA/AI technologies and tools.

Key Skills:

Technical Expertise:

• Advanced knowledge of Python and Linux shell scripting
• Experience with SQL/NoSQL databases
• Strong proficiency in Python (pandas, NumPy, PySpark preferred).
• Experience with SQL and at least one cloud data warehouse (Databricks, AWS Redshift, Google BigQuery, Snowflake, etc.).
• Hands-on experience with ETL tools or orchestration frameworks (Airflow, dbt, AWS Glue, etc.).
• Exposure to AI/ML pipelines or data for LLM applications is an advantage.
• Familiarity with data APIs, REST integrations, and data ingestion from SaaS tools.
• Understanding of data modeling, normalization, and schema design.
• Proficiency in building stream processing systems using Kafka
• Experience with modern data stack technologies.
• Strong understanding of data governance principles and practices.
• Experience in implementing CI/CD pipelines for data engineering processes.
• Experience with data migration strategies and tools.

Problem-Solving and Analytical Skills:

• Strong ability to troubleshoot and resolve technical issues.
• Analytical mindset with a focus on delivering measurable results.

Nice to have Skills:

• Strong communication and collaboration skills
• Experience working in Agile or startup environments.
• Having authored articles /thought leadership on Data Management trends and technologies
• People Management and Capability development