Enterprise solutions architect

4 days ago

Chennai, India Mphasis Full time

Job Description Role: Enterprise Architect Who are we looking for? As a Senior Data Architect in the BFSI domain, you will be responsible for designing and governing data architecture across core banking, Wealth Management and financial platforms. You’ll lead initiatives that span legacy systems (mainframes) to modern cloud-native and No SQL solutions, ensuring regulatory compliance, data lineage, and high availability for mission-critical applications. Domain Expertise: Deep understanding of BFSI data domains : customer, account, transaction, trading, portfolios, positions, credit, risk, claims, policy, and underwriting. Experience with financial data modeling , including ledger structures , risk hierarchies , and regulatory taxonomies . Data Modeling & Architecture: Proficiency in Erwin , Power Designers , or Toad Data Modeler . Experience with 3 NF , dimensional modeling , data vault , and canonical models . Key Responsibilities: Architect scalable data solutions for core banking , Wealth Management , risk management , fraud detection , and regulatory reporting . Design data models for transactional systems, data warehouses, and real-time analytics platforms. Lead data migration from legacy systems (e.g., DB2, VSAM) to cloud platforms like Snowflake , Azure Synapse , or Google Big Query. Lead Data migration from Oracle to Postgres, SQL Server to Postgres Collaborate with compliance teams to ensure data governance , auditability , and regulatory alignment (e.g., Basel III, IFRS, GDPR). Build and optimize ETL/ELT pipelines for high-volume financial data using tools like Informatica , Talend , Apache Ni Fi , or Azure Data Factory . Integrate data across core banking systems , Wealth Management Systems , CRM , insurance platforms , and digital channels . Define metadata standards, lineage tracking, and master data management frameworks. Mentor data engineers and analysts; contribute to architectural reviews and BFSI-specific best practices. Knowledge & Skills: Databases & Platforms: Category Technologies Mainframe - IBM DB2, IMS, VSAM Relational - Oracle, SQL Server, Postgre SQL, No SQL - Mongo DB, Cassandra, Couchbase, Aerospike Cloud DBs - Snowflake, Redshift, Big Query, Azure Synapse, Yugabyte Data Lakes - Hadoop, Azure Data Lake, Amazon S3 Tools - SQL server Management Studio, TOAD, Foglight, Boost, Studio 3 T ETL & Streaming: Informatica , Talend, Apache Ni Fi, Azure Data Factory, IICS, Airflow and DBT Kafka , Spark Streaming, Flink for real-time data ingestion Cloud & Dev Ops: Hands-on with GCP data services AWS , Azure Familiarity with Terraform , Git , CI/CD , Docker , Kubernetes Governance & Security: Tools: Collibra, Alation, Apache Atlas Practices: Data lineage, masking, encryption, RBAC, audit trails Programming & Scripting: SQL, Python, Shell scripting, Scala (optional)

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