Azure Data Architect

Job description

The Azure Data Solutions Architect leads the design and implementation of enterprise-scale data solutions using Azure Data Factory, Azure Databricks, and Azure Synapse Analytics. This role provides architectural leadership, ensuring solutions are robust, scalable, and aligned with business strategy and industry best practices. The architect drives innovation, enforces governance, and mentors teams to deliver high-quality, future-ready data platforms that support organizational transformation. Key Responsibilities Key Responsibilities: Design and implement scalable data architectures using Azure services Build and optimize ETL/ELT pipelines using Azure Databricks and Apache Spark Architect data lake and data warehouse solutions using Azure Data Lake and Azure Synapse Analytics Define data modeling strategies (batch & real-time processing) Ensure data security, governance, and compliance standards Collaborate with stakeholders to understand business requirements and translate them into technical solutions Optimize performance and cost efficiency of data workloads Implement CI/CD pipelines for data engineering workflows Mentor and guide data engineers and development teams Integrate advanced analytics, AI, and ML solutions when required Skill Requirements Required Skills & Qualifications: Strong experience with Azure Databricks and Spark (PySpark/Scala) Hands-on experience with Azure services (ADF, ADLS, Synapse, Event Hub) Expertise in big data architecture and distributed systems Strong knowledge of SQL, Python, and data engineering concepts Experience with data modeling techniques (star schema, dimensional modeling) Understanding of real-time streaming (Kafka/Event Hub) Knowledge of DevOps and CI/CD practices Strong Development Area: Data Engineering Foundations Batch vs streaming; lakehouse concepts; medallion (Bronze/Silver/Gold); file formats (Parquet/Delta/CSV/JSON/Avro); partitioning & clustering; schema evolution; data governance basics; DevOps/CI-CD for data. SQL Joins, subqueries, CTEs, window functions, set operations; aggregation & rollups; MERGE/UPSERT; analytic functions; performance (indexes, partition pruning, statistics); data validation scenarios (dedupe, top-N, SCD keys). Apache Spark (Core) Spark architecture (driver/executors), DAG, stages/tasks; RDD vs DataFrame/Dataset; wide vs narrow transformations; shuffle mechanics; caching/persistence; partitioning; broadcast joins; skew handling; checkpointing; job tuning. PySpark DataFrame API, Spark SQL; UDF vs pandas UDF; windowing; incremental loads; structured streaming (triggers, watermarks); handling semi-structured data; optimizing with predicates, pushdown, join strategies; error handling; unit testing (pytest + chispa). Databricks Platform Workspace basics; clusters (Single Node/All-Purpose/Jobs), cluster policies; DBR/LTS; notebooks & Repos; Jobs & Workflows; Delta Lake & Delta Live Tables; Unity Catalog (catalog/schema/table, permissions, lineage); MLflow basics; secret scopes; DBFS; REST APIs; Databricks Connect. Delta Lake / Lakehouse Patterns ACID transactions; schema enforcement/evolution; time travel; OPTIMIZE/ZORDER; VACUUM; CDC patterns (MERGE INTO, change data feed); streaming vs batch Delta; expectations/constraints; table maintenance strategies. Orchestration & Scheduling Databricks Workflows; Azure Data Factory/Synapse pipelines; triggers; parameter passing; fail/retry; alerts; integration with AutoSys/Control-M/Jenkins/GitHub Actions; event-driven patterns. Python (Core for Data) Core syntax; typing & data structures; file I/O; logging; virtual environments; packaging; testing (pytest); common data libs (pandas, pyarrow); error handling; performance considerations (vectorization, generators). Data Quality & Testing Great Expectations/dbx expectations or custom checks; unit/integration tests; reconciliation (row/amount); anomaly detection; contract testing for schemas; data observability (metrics, SLAs, freshness). Security & Governance Unity Catalog permissions, row/column-level security; secrets management (Key Vault/Secret scopes); PII handling; audit logs; token management; compliance basics. Cost & Performance Optimization Cluster sizing, autoscaling; DBU awareness; spot/preemptible instances; storage formats; caching; efficient joins; job scheduling; monitoring with metrics & Ganglia/Spark UI; cost tagging and chargeback. Analytical Skills & Problem Solving Break down data problems; root-cause incidents; propose alternatives; estimate complexity; communicate clearly with stakeholders. Stake Holder Management Interaction with Client Stakeholders, Communication. Other Requirements 1. Microsoft Certified: Azure Solutions Architect Expert (Recommended) 2. Microsoft Certified: Azure Data Engineer Associate (Optional But Valuable Apply now Information at a Glance Why HCLTech? At HCLTech, you'll supercharge your potential. You'll find your career. And you'll find your spark. All at a place that knows that helping its customers stay on top starts by putting its people first. HCLTech is a global technology company, home to more than 223,000 people across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud and AI, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of 12 months ending June 2026 totaled $14.8 billion. Disclaimer Privacy Statement Terms of use Sitemap Raise a Grievance We use cookies on our site. Please read more about cookies policy here. Opens in a new tab. Opens in a new tab. Opens in a new tab. Opens in a new tab. Opens in a new tab. Opens in a new tab. Copyright © 2026 HCL Technologies Limited Cookie Consent Manager When you visit any website, it may store or retrieve information on your browser, mostly in the form of cookies. Because we respect your right to privacy, you can choose not to allow some types of cookies. However, blocking some types of cookies may impact your experience of the site and the services we are able to offer. Required Cookies These cookies are required to use this website and can't be turned off. Required Cookies Required Cookies Provider Description Enabled SAP as service provider We use the following session cookies, which are all required to enable the website to function: "route" is used for session stickiness "careerSiteCompanyId" is used to send the request to the correct data center "JSESSIONID" is placed on the visitor's device during the session so the server can identify the visitor "Load balancer cookie" (actual cookie name may vary) prevents a visitor from bouncing from one instance to another Cookies from provider SAPasserviceprovider are required and cannot be turned off Functional Cookies These cookies provide a better customer experience on this site, such as by remembering your login details, optimizing video performance, or providing us with information about how our site is used. You may freely choose to accept or decline these cookies at any time. Note that certain functionalities that these third-parties make available may be impacted if you do not accept these cookies. Consent to all Functional Cookies Functional Cookies Provider Description Enabled Vimeo Vimeo is a video hosting, sharing, and services platform focused on the delivery of video. Opting out of Vimeo cookies will disable your ability to watch or interact with Vimeo videos. Cookie Policy Privacy Policy Terms and Conditions Consent to cookies from provider Vimeo YouTube YouTube is a video-sharing service where users can create their own profile, upload videos, watch, like, and comment on videos. Opting out of YouTube cookies will disable your ability to watch or interact with YouTube videos. Cookie Policy Privacy Policy Terms and Cond