Presto Developer

Elfonze Technologies; Bengaluru; On-site; INR 1,800,000 - 2,800,000; Full time

Job summary

Elfonze Technologies in Bengaluru, India, is seeking a senior Data Engineer to own and optimize large-scale data pipelines and analytics workloads. You will design ELT pipelines with SQL, Python, PySpark, and manage lakehouse architectures across Snowflake and PrestoDB, while ensuring data quality and governance.

You will collaborate in Agile sprints, build Looker models and Tableau data sources, and apply dbt and Airflow for orchestration, Kafka for streaming, and cloud storage (S3/ADLS) in

Qualifications

• 6 years of hands-on Data Engineering experience with expert-level proficiency in SQL and Python (Pandas, PySpark)
• Strong operational knowledge of Snowflake and PrestoDB for complex, large-scale query processing
• Practical experience with AWS or Azure services, cloud storage (S3/ADLS), and columnar/open table formats (Apache Iceberg, Delta Lake, Parquet)
• Hands-on experience developing Looker models (LookML, PDTs) and constructing Tableau dashboards & reporting
• Solid background in dbt for transformation, Apache Airflow for workflow DAG management, and familiarity with Apache Kafka for event streaming platforms
• Understanding of data preparation requirements for statistical models, machine learning frameworks, and regression/tree-based algorithms

Responsibilities

• ELT Pipeline Engineering: Design, build, and maintain high-throughput batch and streaming ETL/ELT data pipelines using SQL, Python, and PySpark to ingest large datasets into cloud data lakes and Snowflake
• Lakehouse & Federated Query Operations: Manage and optimize data structures across AWS/Azure storage (S3/ADLS) using open table formats (Apache Iceberg, Delta Lake) and execute cross-platform queries via Presto/Trino
• Query & Warehouse Optimization: Diagnose performance bottlenecks, optimize SQL queries, and configure Presto/Trino execution parameters alongside Snowflake virtual warehouse sizing/clustering to reduce compute costs and query latency
• BI & Semantic Layer Development: Build and maintain scalable data models, Looker semantic layers (LookML), and curated Tableau data sources to enable self-service business intelligence and executive reporting
• Governance & Access Control: Enforce data security and row/column-level access controls using AWS Lake Formation tag-based policies and Snowflake RBAC, while leveraging OpenSearch for real-time log monitoring and search
• Data Quality & Orchestration: Implement automated pipeline testing, schema validation, and alert monitoring using dbt and Apache Airflow to maintain data freshness and platform integrity
• Agile Delivery & Collaboration: Active participation in Agile sprint ceremonies, performing code reviews, creating technical architecture documentation, and collaborating with senior engineers on platform features

Skills

SQL

Python (Pandas PySpark)

Snowflake

PrestoDB

Looker LookML

Tableau

dbt

Apache Airflow

Apache Kafka

AWS / Azure

Iceberg

Delta Lake

Parquet

Education

Degree in Data Science, Analytics, Computer Science

Tools

Snowflake

PrestoDB

Looker

Tableau

dbt

Airflow

Kafka

S3/ADLS

Iceberg

Delta Lake

Parquet

Job description

Presto Job Description:

Responsibilities

• ELT Pipeline Engineering: Design, build, and maintain high-throughput batch and streaming ETL/ELT data pipelines using SQL, Python, and PySpark to ingest large datasets into cloud data lakes and Snowflake
• Lakehouse & Federated Query Operations: Manage and optimize data structures across AWS/Azure storage (S3/ADLS) using open table formats (Apache Iceberg, Delta Lake) and execute cross-platform queries via Presto/Trino
• Query & Warehouse Optimization: Diagnose performance bottlenecks, optimize SQL queries, and configure Presto/Trino execution parameters alongside Snowflake virtual warehouse sizing/clustering to reduce compute costs and query latency
• BI & Semantic Layer Development: Build and maintain scalable data models, Looker semantic layers (LookML), and curated Tableau data sources to enable self-service business intelligence and executive reporting
• Governance & Access Control: Enforce data security and row/column-level access controls using AWS Lake Formation tag-based policies and Snowflake RBAC, while leveraging OpenSearch for real-time log monitoring and search
• Data Quality & Orchestration: Implement automated pipeline testing, schema validation, and alert monitoring using dbt and Apache Airflow to maintain data freshness and platform integrity
• Agile Delivery & Collaboration: Active participation in Agile sprint ceremonies, performing code reviews, creating technical architecture documentation, and collaborating with senior engineers on platform features

Qualifications

Technical Expertise:

• Core Skills & Languages: Minimum 6 years of hands-on Data Engineering experience with expert-level proficiency in SQL and Python (Pandas, PySpark)
• Engine & Warehouse Expertise: Strong operational knowledge of Snowflake and PrestoDB for complex, large-scale query processing
• Cloud & Lakehouse Architecture: Practical experience with AWS or Azure services, cloud storage (S3/ADLS), and columnar/open table formats (Apache Iceberg, Delta Lake, Parquet)
• BI & Analytics: Hands-on experience developing Looker models (LookML, PDTs) and constructing Tableau dashboards & reporting
• Transformation & Streaming: Solid background in dbt for transformation, Apache Airflow for workflow DAG management, and familiarity with Apache Kafka for event streaming platforms
• Applied Data Science Familiarity: Understanding of data preparation requirements for statistical models, machine learning frameworks, and regression/tree-based algorithms

Education & Experience:

• Degree in Data Science, Analytics, Computer Science, or a related quantitative field
• 6 years of progressive experience building, maintaining, and supporting production data platforms