Senior Developer, Snowflake, Databricks

Jobtailor

Gurugram District

On-site

INR 2,000,000 - 3,600,000

Full time

14 days+

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Job summary

Jobtailor in Gurugram (India) seeks an experienced Data Engineer to design, develop, and optimize large-scale cloud data pipelines using Databricks and Snowflake. You’ll work on PySpark applications, Delta Lake tables, and Snowflake SQL, enabling efficient ELT workflows and data integration across cloud platforms.

The role requires strong hands-on skills with Databricks, PySpark, Delta Lake, Snowflake, and ADF/Synapse.

Qualifications

Bachelor's degree in Computer Science or Information Technology (or related field).
4+ years of experience in data engineering or big data development.
3+ years hands-on with Databricks, PySpark, and Azure Data Engineering.
3+ years hands-on with Snowflake, Snowflake SQL, and ELT development.
Strong hands-on experience with Databricks, PySpark, Delta Lake, and Spark SQL.
Experience with ADF, Synapse, and ADLS integrations.
Expertise in Snowflake SQL, performance tuning, and warehousing.
Experience with Snowpipe, Streams, Tasks, and orchestration via ADF/Synapse.
Knowledge of RBAC, masking policies, and security best practices.
Strong understanding of data warehousing concepts and cloud data architecture.
Familiarity with CI/CD, Azure DevOps/GitHub Actions, and Git workflows.
Strong analytical and problem-solving abilities.
Excellent communication and stakeholder management.
Ability to work independently and collaboratively in agile teams.

Responsibilities

Design, develop, optimize, and maintain large-scale cloud data pipelines across Databricks and Snowflake.
Develop and optimize Databricks Notebooks, Workflows, Jobs, PySpark applications, data transformations, and Delta Lake tables.
Develop and optimize Snowflake SQL, including complex joins, window functions, and CTEs.
Build and manage Snowflake pipelines using Stages, File Formats, COPY, and Snowpipe.
Implement Streams, Tasks, and Materialized Views for automated ELT workflows.
Perform Snowflake performance tuning, virtual warehouse optimization, and cost governance.
Design and build ETL/ELT pipelines integrating Databricks, Snowflake, Azure Data Factory, Spark, SQL, ADF, and Synapse.
Integrate data from relational databases, APIs, file systems, and cloud platforms.
Align solutions with enterprise data architecture and modeling standards.
Document pipelines, workflows, data models, and architecture.
Ensure compliance with governance, security, and regulatory standards.
Gather data requirements from business stakeholders and convert them into technical solutions.
Support BI, analytics, and downstream consumers.
Debug Databricks notebooks, Spark jobs, and ADF pipelines.
Troubleshoot Snowflake execution errors, warehouse performance problems, and ingestion failures.
Perform root-cause analysis and implement preventive measures.
Collaborate with data engineers, analysts, architects, and business stakeholders.

Skills

Databricks

PySpark

Azure Data Engineering

Snowflake SQL

ETL/ELT Development

Education

Bachelor's degree in Computer Science or Information Technology

Tools

Databricks Notebooks

Snowflake

Delta Lake

Spark SQL

Azure Data Factory (ADF)

Synapse

ADLS

GitHub Actions

CI/CD

Job description

Design, develop, optimize, and maintain large-scale cloud data pipelines across Databricks and Snowflake
Develop and optimize Databricks Notebooks, Workflows, Jobs, PySpark applications, data transformations, and Delta Lake tables
Develop and optimize Snowflake SQL, including complex joins, window functions, and CTEs
Build and manage Snowflake pipelines using Stages, File Formats, COPY, and Snowpipe
Implement Streams, Tasks, and Materialized Views for automated ELT workflows
Perform Snowflake performance tuning, virtual warehouse optimization, and cost governance
Design and build ETL/ELT pipelines integrating Databricks, Snowflake, Azure Data Factory, Spark, SQL, ADF, and Synapse
Integrate data from relational databases, APIs, file systems, and cloud platforms
Align solutions with enterprise data architecture and modeling standards
Document pipelines, workflows, data models, and architecture
Ensure compliance with governance, security, and regulatory standards
Gather data requirements from business stakeholders and convert them into technical solutions
Support BI, analytics, and downstream consumers
Debug Databricks notebooks, Spark jobs, and ADF pipelines
Troubleshoot Snowflake execution errors, warehouse performance problems, and ingestion failures
Perform root-cause analysis and implement preventive measures
Collaborate with data engineers, analysts, architects, and business stakeholders

Requirements

Bachelor's degree in Computer Science, Information Technology, or related field (or equivalent experience)
4+ years of experience in data engineering or big data development
3+ years hands-on with Databricks, PySpark, and Azure Data Engineering
3+ years hands-on with Snowflake, Snowflake SQL, and ELT development
Strong hands-on experience with Databricks, PySpark, Delta Lake, and Spark SQL
Experience with ADF, Synapse, and ADLS integrations
Expertise in Snowflake SQL, performance tuning, and warehousing
Experience with Snowpipe, Streams, Tasks, and orchestration via ADF/Synapse
Knowledge of RBAC, masking policies, and security best practices
Strong understanding of data warehousing concepts and cloud data architecture
Familiarity with CI/CD, Azure DevOps/GitHub Actions, and Git workflows
Strong analytical and problem-solving abilities
Excellent communication and stakeholder management
Ability to work independently and collaboratively in agile teams

Core Competencies

Demonstrates expertise in designing and optimizing large-scale cloud data pipelines using Databricks and Snowflake, with a strong focus on performance tuning, ELT development, and data integration. Proficient in collaborating with stakeholders to gather requirements and ensure compliance with governance and security standards.

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