Principal Data Architect
Evoke Technologies
- Location
- Hyderabad, Telangana, India
- Job type
- Full-time
Required skills
- Python
- Airflow
- AWS
- business analytics
- CloudFormation
- data architecture
- data solutions
- data warehouse
- Databricks
- ETL
- GitHub
- infrastructure-as-code
- Lambda
- metadata management
- MySQL
- Postgres
- Serverless
- Snowflake
- SQL
- Terraform
About the role
Evoke Technologies
Website:
evoketechnologies.com
Job details:
Key Responsibilities
- 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
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