Job Type: Permanent
Work Mode: Hybrid (2 Days from office)
* Architect and design end-to-end Azure data engineering solutions (batch + near real-time) aligned to enterprise standards.
* Define target state architecture for data ingestion, transformation, orchestration, and serving layers.
* Lead architectural decisions around scalability, resiliency, performance, security, governance, and cost optimization.
* Design, develop, test, and deploy Azure Data Factory pipelines following best practices (modular design, parameterization, reusability, CI/CD readiness).
* Build robust ingestion and orchestration workflows using:
o Mapping Data Flows / Wrangling Data Flows (where applicable)
* Implement operational excellence: logging, alerting, retry patterns, failure handling, and idempotent design.
SQL Development & Optimization
* Develop and optimize SQL queries and stored procedures to support ADF pipeline operations and downstream transformations.
* Conduct query plan analysis and performance tuning (indexes, partitioning strategies, statistics, query rewrites).
* Establish SQL coding standards and reusable patterns for transformation logic.
Troubleshooting & Analytical Problem Solving
* Apply a strong analytical mindset to diagnose and resolve complex data integration issues across ingestion, transformation, orchestration, and storage layers.
* Perform root cause analysis (RCA) for pipeline failures, performance degradation, data quality issues, and environment instability.
* Design proactive monitoring dashboards and alerts for pipeline SLAs and data freshness.
* Define and enforce best practices for:
o CI/CD for ADF (Azure DevOps / Git-based workflows)
o Infrastructure-as-Code (ARM/Bicep/Terraform—preferred)
o Version control, code review, release management
* Implement data governance patterns: metadata management, lineage, auditing, encryption, RBAC, key management, PII controls.
* Collaborate with security/compliance teams to ensure enterprise adherence.
Leadership & Stakeholder Management
* Act as a technical leader for data engineering squads; mentor and guide engineers on design patterns and implementation.
* Translate business requirements into technical architecture and delivery plans.
* Work closely with Product Owners, Data Analysts, Data Scientists, and Platform teams to ensure alignment.
Required Skills & Qualifications
Must-Have (Strong)
* 12–16 years of overall IT experience with significant data engineering & architecture exposure.
* Strong Azure Cloud Data Engineering and associated services architecture knowledge.
* Deep hands-on experience with:
o SQL – advanced querying, stored procedures, performance tuning
* Strong troubleshooting skills for complex multi-system data issues.
* Strong understanding of data architecture concepts:
o Data lakes/lakehouse/warehouse, dimensional modeling, ELT/ETL patterns
Azure Ecosystem (Preferred / Good to Have)
* Azure data services experience in one or more:
* Monitoring & observability:
* Security & identity:
* CI/CD practices for data pipelines; Git branching strategies and release governance.
Behavioral / Soft Skills
* Excellent analytical thinking and structured problem-solving.
* Strong communication and stakeholder management skills.
* Ownership mindset, ability to drive standards and influence cross-team adoption.
* Proven mentoring/coaching ability.
Education
* Bachelor’s/Master’s degree in Computer Science, Information Systems, or related field (or equivalent experience).
Nice-to-Have Certifications
* Microsoft Certified: Azure Data Engineer Associate
* Microsoft Certified: Azure Solutions Architect Expert
What Success Looks Like (Outcome Focus)
* Highly reliable ADF pipelines with strong observability, error handling, and SLA adherence.
* Measurable improvements in SQL performance and pipeline execution time.
* Standardized architecture patterns adopted across teams.
* Reduced incident rates through proactive monitoring and strong RCA discipline.
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