Sr. Data Engineer

Role:
Sr. Data Engineer

Location:
Bangalore - Onsite

Duration:
Full-Time

Timings:
1-10 PM IST (Cab; Food & other facilities provided)

Experience:
6-8 yrs

Skills to crack:
Snowflake, SQL, Python, ETL, Apache Airflow

Desired Skills:
PowerBI, CRM (Salesforce), ERP (Oracle)

About the Role:

• We are seeking an experienced and proactive Senior Data Engineer to drive the design, development, and optimization of our enterprise data infrastructure, with a core focus on
  Snowflake
  .
• You will lead complex data integration projects from CRM (preferably Salesforce), ERP systems (such as Oracle), and other enterprise sources.
• This role will play a critical part in shaping our data platform, ensuring scalability, performance, and compliance to support advanced analytics and AI initiatives.

Required Qualifications:

• Bachelor's or Master's degree in computer science, Engineering, Information Systems, or a related technical field.
• 6+ years of hands-on experience as a Data Engineer, with a proven track record of delivering production-grade data solutions.
• Expertise in
  Snowflake
  : performance tuning, data modelling, security features, and best practices.
• Deep experience integrating complex systems like CRM (Salesforce) and ERP platforms (NetSuite, etc.).
• Advanced proficiency in
  SQL
  , including optimization, CTEs, window functions, and complex joins.
• Strong experience with
  Python
  for building and orchestrating data pipelines.
• Expertise with data pipeline tools or custom-built
  ETL
  frameworks.
• Solid experience in
  cloud
  ecosystems (AWS, Azure, GCP) — including storage, compute, and serverless services.
• Strong understanding of data governance, metadata management, and data cataloguing solutions.
• Certifications in Snowflake, Salesforce Data Architecture, or Cloud Architect certifications (AWS, Azure, GCP).
• Experience working with real-time data ingestion tools (Kafka, Kinesis, Pub/Sub).
• Knowledge of Data Lakehouse architecture and experience with Delta Lake, Apache Iceberg, or similar technologies.
• Familiarity with ML Ops or supporting Data Science initiatives is a plus.

Responsibilities:

• Architect, develop, and optimize highly scalable, reliable, and secure data pipelines and workflows on Snowflake.
• Lead and oversee the integration of data from CRM (Salesforce), ERP platforms, and other third-party systems into the enterprise data warehouse.
• Define best practices for data modelling, data quality, security, and operational efficiency.
• Collaborate with cross-functional teams (Product, Engineering, BI, Data Science) to understand business needs and deliver comprehensive data solutions.
• Mentor and guide junior and mid-level data engineers through code reviews, technical guidance, and architectural discussions.
• Evaluate and recommend modern data tools, frameworks, and patterns (e.g., ELT, Data Mesh, Data Vault modelling).
• Implement and manage orchestration tools and CI/CD pipelines for data engineering projects.
• Own monitoring, logging, and alerting strategies for data pipelines, ensuring high uptime and performance.
• Ensure compliance with data governance, privacy, and security standards (GDPR, HIPAA, SOX).
• Contribute to technical documentation, runbooks, and knowledge-sharing initiatives within the team.

Soft Skills:

• Strong leadership capabilities with a hands-on attitude.
• Excellent problem-solving and decision-making abilities.
• Strong written and verbal communication skills — able to explain technical concepts to business stakeholders.
• Ability to balance speed and quality, pushing for sustainable engineering excellence.
• A mindset of continuous learning and innovation.