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Data Engineer with 3+ years in Azure, PySpark & Delta Lake
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Assessing your cultural and operational fit
Azure Data Engineer with 3 years of experience delivering end-to-end data pipelines across BFSI and telecom domains — building 20+ ADF pipelines, processing millions of daily subscriber records, and resolving 50+ production incidents at Accenture. Hands-on in Azure Databricks, PySpark, ADLS Gen2, and Delta Lake across medallion architecture design, Bronze-to-Silver transformations, CDC-based processing, and SCD Type 2 tracking. Currently owning full-lifecycle development of a 9-source banking data platform at Eagle Drift, from Azure infrastructure provisioning to Customer 360 feature engineering.
Chaitanya Bharati Institute of Technology
B. Tech · Computer Science and Engineering
August 1, 2017 – June 30, 2021
Eagle Drift Technologies
Azure Data Engineer Databricks Development & Pipeline Support
March 1, 2026 – Present
Bhubaneshwar, Odisha, India
Accenture Solutions
Data Engineering Analyst ETL Development & Production Support
July 1, 2021 – March 1, 2024
Hyderābād, Telangana, India
Banking AI Recommendation Platform
March 1, 2026 – Present
Built an end-to-end Azure banking data platform across 9 source domains (customer profiles, transaction history, online banking activity, mobile app events, service interactions, product catalog, and market data) to power personalised product recommendations for a 2–5 person engineering team. Created all Azure resources from scratch via Azure CLI; configured RBAC assignments, external locations, and Databricks-to-ADLS connectivity using Managed Identity and Key Vault-backed secrets. Designed ADLS Gen2 storage with domain-aligned paths and date-partitioned folders across 9 domains (raw/customer_profile, raw/transaction_history, etc.) to support incremental ingestion and batch-level traceability. Developed a unified PySpark notebook to ingest all 9 raw CSV and JSON datasets (~500K-1M rows total), convert to Delta format, and write structured output to the Bronze layer in a single orchestrated run. Currently building Bronze-to-Silver notebooks covering data cleaning, SHA-256 PII masking, duplicate removal on transaction IDs, null handling, and Customer 360 feature engineering (spend bands, age bands, income bands, credit score ranges, and digital engagement scores). Planned downstream components: Azure AI Language for NLP intent/sentiment extraction, a rule-based scoring engine across 6 banking products, Azure OpenAI for explanation generation, and compliance validation before recommendations reach consumers.
Telecom Data Processing System Ab Initio to Azure Migration
July 1, 2021 – March 1, 2024
Developed 15+ parameterized ADF ingestion pipelines to pull prepaid and postpaid telecom subscriber and usage files landing from upstream file systems into ADLS Gen2, running on daily schedules. Built PySpark and Spark SQL transformations processing millions of subscriber records daily - covering data cleaning, usage aggregations, incremental loads, CDC flows, and SCD Type 2 tracking for accurate historical plan and status records. Mapped legacy Ab Initio ETL graphs to equivalent PySpark logic; validated migrated outputs against Ab Initio reference results using record counts, duplicate checks, null checks, reconciliation, and business-rule validation across all migrated workflows. Triaged and resolved 50+ production incidents over 2.5 years - covering missing files, storage path errors, schema changes, and data-quality failures – maintaining RCA records in Jira and Confluence with zero missed SLA escalations. Delivered analytics-ready datasets for downstream reporting; improved Spark job performance by pushing filter predicates earlier and eliminating unnecessary column scans.
Cultural Fit Analysis
The candidate's experience across banking and telecom domains, coupled with a focus on end-to-end data platform development and production support, aligns well with roles requiring robust, reliable data solutions. Their proactive approach to infrastructure provisioning and data quality validation indicates a strong sense of ownership. The breadth of skills in Azure, Spark, and ETL methodologies suggests a versatile and adaptable individual who can contribute to diverse projects and team environments.
Soft Skills & Operational Fit
The candidate demonstrates strong operational discipline through extensive production support experience, including triaging and resolving 50+ incidents with zero missed SLA escalations. Their ability to document RCA records in Jira and Confluence indicates good communication and organizational skills. The experience in a 2-5 person engineering team suggests adaptability and collaboration. The promotion within one year at Accenture highlights a strong work ethic and performance.