Syren Technologies
Data Architect
- Compensation
- Not disclosed
- Location
- Hyderabad
- Work setup
- Remote
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Architecture
- Posted
Skills
Nice to have
- Strong experience in data architecture, data platform design, or enterprise data engineering.
- Hands-on experience with Databricks and cloud-based data platforms.
- Strong expertise in at least one cloud platform: Microsoft Azure, AWS, or GCP.
- Solid understanding of lakehouse architecture, Delta Lake, and the Medallion Architecture.
- Proficiency in SQL and practical knowledge of Python, PySpark, and Apache Spark.
- Experience designing data models, data pipelines, and data integration solutions.
- Understanding of data governance, security, access management, data quality, and metadata management.
- Experience with performance tuning, scalability, reliability, and cost optimization of data platforms.
- Ability to translate business and technical requirements into scalable architectural solutions.
- Strong communication, problem-solving, stakeholder management, and technical documentation skills.
Full description
Role & responsibilities:
- Design and implement scalable, secure, and cost-effective data architectures using Databricks on Azure, AWS, or GCP.
- Define end-to-end lakehouse architecture, including data ingestion, transformation, storage, processing, and consumption layers.
- Develop architecture standards and best practices for data engineering, data modelling, data integration, and platform design.
- Leverage Databricks capabilities, including Delta Lake, Unity Catalog, and the Medallion Architecture, wherever appropriate.
- Design and optimize batch and streaming data pipelines using Apache Spark, PySpark, SQL, and related technologies.
- Establish data governance, security, access control, data quality, metadata management, and lineage practices.
- Collaborate with data engineers, analytics teams, business stakeholders, and cloud/platform teams to deliver reliable data solutions.
- Identify and resolve architectural challenges related to scalability, performance, reliability, and cloud cost optimization.
- Evaluate existing data platforms and recommend modernization, migration, and optimization strategies.
- Document architecture designs, technical standards, data flows, and implementation guidelines.
Preferred candidate profile :
- Strong experience in data architecture, data platform design, or enterprise data engineering.
- Hands-on experience with Databricks and cloud-based data platforms.
- Strong expertise in at least one cloud platform: Microsoft Azure, AWS, or GCP.
- Solid understanding of lakehouse architecture, Delta Lake, and the Medallion Architecture.
- Proficiency in SQL and practical knowledge of Python, PySpark, and Apache Spark.
- Experience designing data models, data pipelines, and data integration solutions.
- Understanding of data governance, security, access management, data quality, and metadata management.
- Experience with performance tuning, scalability, reliability, and cost optimization of data platforms.
- Ability to translate business and technical requirements into scalable architectural solutions.
- Strong communication, problem-solving, stakeholder management, and technical documentation skills.