Principal Data Architect

Evoke Technologies; Hyderabad; On-site; INR 3,000,000 - 7,000,000; Full time

Job summary

Evoke Technologies is seeking a senior Data Engineer in Hyderabad to own data warehouse architecture and production ETL/ELT pipelines. You will design scalable data pipelines using PySpark and Python, manage Airflow workflows, and ensure reliable, analytics-ready datasets across core environments.

The role requires 10+ years of data engineering experience, deep SQL tuning, and hands-on work with Terraform, Snowflake, Redshift, DBT, and AWS services.

Qualifications

• 10+ years of experience in data engineering and data warehouse development.
• Strong SQL development skills with performance tuning on RDBMS.
• Mandatory experience with Terraform, Airflow, Snowflake, Redshift, DBT, Python, and PySpark.
• Hands-on experience with AWS Glue, EMR, and Lambda for scalable pipelines.
• Bachelor's or Master's degree in CS/IT or related field.
• Experience delivering enterprise-scale data warehouses and data marts.

Responsibilities

• Own production ETL/ELT performance and environment-level resource management.
• Design, build, and optimize data pipelines for scalability and reliability.
• Lead technical decisions on data architecture and mentor junior/mid-level engineers.
• Collaborate with analytics, product, and business teams to align data solutions with needs.
• Migrate POC pipelines to production-ready processes.

Skills

Data warehousing

SQL performance

Mentoring

Leadership

ETL design

Python

PySpark

Airflow

Terraform

Snowflake

Redshift

DBT

AWS Glue

EMR

Lambda

Databricks

Spark

GitHub Actions

GitLab

Education

Bachelor's or Master's in CS/IT

Tools

Postgres

MySQL

Job description

• Ownership of Data Warehouse models and curation (Snowflake, Redshift, DBT)
• Design, build, and optimize data pipelines using PySpark and Python for scalability and reliability
• Implement and manage workflow orchestration with Airflow for scheduling and automation
• Manage infrastructure-as-code with Terraform to ensure reproducibility and reliability of data environments
• Build and manage serverless and distributed data processing workflows using AWS Glue, EMR, and Lambda
• Drive the evolution of the data environment to deliver high-quality data, speed, and availability
• Curate source-system data — including RDBMS sources — to deliver trusted, analytics-ready datasets
• Provide input and involvement on data cataloging and data management efforts
• Own production ETL/ELT performance tuning and environment-level resource consumption and management
• Drive the migration of POC pipelines to production-ready processes
• Lead technical decision-making on data architecture and mentor junior/mid-level engineers
• Collaborate with analytics, product, and business teams to ensure data solutions align with organizational needs

Qualifications

• 10+ years of experience in data engineering and data warehouse development
• Strong SQL development skills with expertise in performance tuning on RDBMS (Postgres, MySQL, or similar)
• Mandatory experience with: Terraform, Airflow, Snowflake, Redshift, DBT, Python, and PySpark
• Hands‑on experience with AWS Glue, EMR, and Lambda for building scalable, distributed data pipelines
• Bachelor's or Master's degree in Computer Science, Information Technology, or related field
• Proven experience designing and delivering enterprise-scale data warehouses and marts to support business analytics
• Experience developing data curation and integration processes, metadata management, and data quality initiatives
• Experience with streaming and real-time data processing (Spark, Databricks optional)
• Familiarity with ETL tools (Fivetran good to have)
• Experience working with broader AWS services — Step Functions, S3, CloudFormation
• Knowledge of CI/CD workflows and source control (GitHub Actions, GitLab)
• Demonstrated experience leading data engineering initiatives or mentoring teams