Data Engineer/Architect
First seen by Alion on Aug 31, 2026.
Position: Data Engineer - Architect
Open Positions: 1
Date: August 2026
Skillset: Azure, Databricks, Snowflake, Spark, PySpark, SQL, Python, ADF/Airflow, Data Modeling, CI/CD, Terraform/Bicep, Data Governance
Experience: 10 to 12+ Years
Requirement: Full-Time
Location: Hyderabad - Work from Office
Company Description:
At NStarX, we live by our mission: being the Lodestar to Success for enterprises navigating the rapidly evolving digital landscape. We build cutting-edge, production-ready platforms that integrate advanced AI, cloud-native architecture, and robust data engineering to solve complex business challenges at scale. If you thrive in a collaborative environment that values technical excellence, architectural ownership, and production-first innovation, NStarX is where your impact will shine.
Job Description:
We are looking for a Data Engineer - Architect who can bridge high-level data strategy with hands-on engineering. The role will own the design, architecture, governance, and technical direction of enterprise-grade data platforms using modern cloud and distributed-computing technologies. The ideal candidate will bring deep experience in Azure data architecture, Databricks/Snowflake, data modeling, orchestration, DevOps, Infrastructure-as-Code, security, performance optimization, and cloud cost management.
Key Responsibilities:
- System Architecture: Design scalable, resilient, secure, and cost-effective data lakehouses and warehouses using modern patterns such as Medallion Architecture (Bronze/Silver/Gold).
- Technical Leadership: Set engineering standards, conduct architecture and code reviews, establish reusable frameworks, and mentor data engineers on best practices.
- Data Enablement: Deliver reliable, high-performance data platforms that support BI, data science, machine learning, and operational analytics.
- Cloud Architecture: Design end-to-end Azure/cloud infrastructure blueprints covering storage, compute, RBAC, security, network isolation, scalability, and cost optimization.
- Big Data & Processing: Architect and optimize Spark/Databricks/Snowflake workloads, including Delta Lake design, cluster sizing, partitioning, Z-Ordering, Vacuuming, clustering, and performance tuning.
- Data Pipelines & Ingestion: Build and standardize production-grade PySpark, Python, and SQL pipelines supporting batch, micro-batch, streaming, and CDC ingestion patterns.
- Data Modeling: Establish organizational data-modeling standards and design Star/Snowflake schemas, Kimball dimensional models, Data Vault patterns, and Lakehouse storage layers.
- Orchestration: Architect workflow dependencies, retries, alerts, monitoring, and backfilling using Azure Data Factory, Airflow, or Databricks Workflows.
- DevOps & CI/CD: Implement Git-based development standards and automated CI/CD pipelines using Azure DevOps or GitHub Actions for reliable data-platform deployments.
- Infrastructure-as-Code: Design and implement infrastructure provisioning using Terraform, Bicep, or equivalent IaC frameworks.
- Governance & Security: Implement metadata catalogs, lineage, data quality controls, access policies, and regulatory compliance practices using technologies such as Unity Catalog and Microsoft Purview.
- Performance & FinOps: Benchmark workloads, resolve bottlenecks, optimize memory and compute configurations, monitor cloud consumption, and drive cost-efficiency across data platforms.
Skills and Experience:
- Overall Experience: 10 to 12+ years of IT/software engineering experience, with at least 5 years in Azure data architecture, cloud platform design, or equivalent data-platform architecture.
- Distributed Computing: 10+ years of experience working with distributed data processing or modern cloud data platforms, with strong hands-on exposure to Databricks, Spark, Snowflake, or equivalent technologies.
- Data Architecture: Strong understanding of Lakehouse/Warehouse architecture, Medallion Architecture, scalability, resiliency, security, and cost optimization.
- Data Modeling: Strong mastery of Kimball dimensional modeling, Star/Snowflake schemas, Data Vault, and analytical data design.
- Programming: Strong hands-on expertise in Python/PySpark and SQL, including production-grade transformations and performance optimization.
- Orchestration: Strong experience with Airflow, Azure Data Factory, Databricks Workflows, or equivalent orchestration platforms.
- DevOps: Hands-on experience with Git, CI/CD, Infrastructure-as-Code, Terraform/Bicep, and automated deployment practices.
- Cloud & Security: Strong understanding of Azure services, RBAC, identity, network isolation, security controls, monitoring, and enterprise governance.
- Communication & Leadership: Ability to communicate architecture decisions clearly, lead technical discussions, mentor engineers, and work effectively with cross-functional stakeholders.
Good to Have:
- Governance: Experience with Unity Catalog, Microsoft Purview, metadata management, data lineage, data quality, GDPR, HIPAA, or other regulated-data environments.
- Monitoring: Experience with Azure Monitor, Log Analytics, operational alerting, and platform observability.
- Cloud Breadth: Exposure to AWS or GCP data platforms in addition to Azure.
- Modern Data Engineering: Experience with CDC, streaming architectures, reusable ingestion frameworks, and platform engineering practices.
Skills
Data Engineering, Data Architect, Data Strategy, Medallion Architecture, DataLake, Data Warehousing, Data Pipeline, Data Ingestion, Python, SQL, Snowflake DB