Data Engineering Consultant Resume
SUMMARY:
- Diligent and result - oriented professional having 6+ years of experience across Design & Development of Data Quality Rule Development & Software Solutions; directing efforts as DQ Consultant with Standard Chartered, Singapore. Experience in architecting the overall DQ design flow E2E & developing Data Quality Rules with use of Oracle EDQ & Informatica IDQ respectively; adept & proficient in using SQL, PL/SQL for database querying.
- Successful track record of spearheading/ developing/ implementing various Data Quality projects within agreed cost/timelines without incidences of overruns, possess extensive knowledge in Analyzing Requirements, Designing, Developing, deploying, Integrating, Testing and Supporting the DQ Applications.
- Enriched with the ability to learn new concepts & technology within a short span of time.
- Excellent communicator, articulate, combined with strong business acumen and logical approach, an ability to handle multiple functions and activities in high pressure environments with tight deadlines.
TECHNICAL SKILLS:
Data Integration: Informatica PowerCenter, Oracle Data Integrator (ODI), Talend Integration Suite
Data Quality: Informatica Data Quality Suite Analyst, Developer (IDQ), Oracle Enterprise Data Quality (OEDQ)
Data Governance: Informatica AXON
Metadata Mgmt. Tools: Informatica Enterprise Data Catalog (EIC), Oracle Enterprise Metadata Management (OEMM)
Big Data Platform: Hadoop 2.x (Platform), HBase, HIVE (hql), Sqoop, Spark, Informatica BDM (Big Data Management)
Business Intelligence: Tableau, Microsoft Power BI, Oracle Business Intelligence Enterprise Edition (OBIEE)
Scripting: VBA (Excel) (Automation / Macros), UNIX Shell Scripting (bash)
Programming: Python, .NET Framework (C#, ASP.NET), Scala
Databases: Oracle Database 11g, Teradata, PostgreSQL
Operating Systems: Solaris (Unix), Linux (Red Hat, Ubuntu), Microsoft Windows 7+
PROFESSIONAL EXPERIENCE:
Confidential
Data Engineering Consultant
Responsibilities:
- Lead the Team in driving the development of IFRS Business Rule Development in EDQ
- Trained Business in Understanding and Developing the Business Rules
- SSE (Self Service Environment) was implemented / deployed by our team and BAU Automation is currently being setup.
- Built E2E Design Flow for IFRS DQ Rule Execution for identifying exceptions & Generating Reports.
- Deployment / Setup of BAU Environment will enable Automation through Control-M and export Exception Records from Oracle DB to Hadoop (hdfs) through Talend ETL. These hdfs files will be consumed as HIVE tables by MSTR Reporting tool.
- Microstrategy (MSTR) Reporting Tool will build Dashboards for Exception Data Reporting to the Management Team.
- Built a Framework Design for handling Retrospective Exception Records' Tracking generated from EDQ Tool.
Environment: Oracle Enterprise Data Quality 12c (EDQ), SQL, PL/SQL, Data Masking, MicroStrategy (Reporting), Teradata (Sourcing DB), Hadoop Platform 2.0, Talend Integration Suite (ETL), HIVE (Tez)
Confidential
Data Engineering ConsultantResponsibilities:
- Build Data Quality Rules to identify exceptions
- Managing Infrastructural control of EDQ Server through WebLogic, not limited to Performance, User/Group Creation(s).
- Report Generation for summarizing exceptions across all levels & segments
Environment: Oracle Enterprise Data Quality 12c, Oracle WebLogic Server 12c, Oracle Database 11g, SQL, PL/SQL, Red Hat Linux 6
Confidential
Data Engineering ConsultantResponsibilities:
- Building New Data Quality Rules across BCRS / CDW Layers
- Trained Business in Understanding and Developing the Business Rules
- Managing Infrastructural control of EDQ Server through WebLogic, not limited to Performance, User/Group Creation(s).
- Rule Enhancements (Promotions) through Change Requests (CRs) and Ongoing Support
Environment: Oracle Enterprise Data Quality 12c, Oracle WebLogic Server 12c, Oracle Database 11g, SQL, PL/SQL, Red Hat Linux 6
Confidential
Data Engineering ConsultantResponsibilities:
- Trained Business in Understanding and Developing the Business Rules
- Managing Infrastructural control of EDQ Server through WebLogic, not limited to Performance, User/Group Creation(s).
- Rule Enhancements (Promotions) through Change Requests (CRs) and Ongoing Support
- Multi Domain being implemented now in Production for separate EDQ Domain for SSE and BAU, after the successful testing of Multiple EDQ Domain Existence in a Single Server through a PoC.
Environment: Oracle Enterprise Data Quality 12c, Oracle WebLogic Server 12c, Oracle Database 11g, SQL, PL/SQL, Red Hat Linux 6
Confidential
Data Engineering Consultant
Responsibilities:
- Designed & Developed Scripts | Jobs in EDQ to carry out the profiling of data for different data fields on source schema tables for different business scenarios and report the statistics to the Business Team.
- Designed & Developed Scripts | Jobs in EDQ to carry out profiling of data on different Data Fields from source schema tables along with the concerned reference tables meant for migration purpose from source to target systems.
- Inconsistent values from the source schema tables were identified & reported which may no longer be supported by the Target Systems.
Environment: Oracle (EDQ), Oracle 11g, SQL, PL/SQL, MS Excel (VBA), UNIX Shell Scripting
Confidential
Data Engineering ConsultantResponsibilities:
- Designed & Developed a Clustering Algorithm to cluster / group similar records for purpose of Matching & Merging.
- Developed Rules for Exact Match & Partial Match Records. Partial Match Rules involved Fuzzy Matching of Records.
- Designed & Developed EDQ scripts for reading the records from Database and output Merged Records for Exact Match Related Parties (RPs) and Partial Matched Records in separate groups, to be sent for review.
Environment: Oracle EDQ, Fuzzy / Advanced Matching Rules, Oracle 11g, SQL, PL/SQL , MS Excel (VBA), UNIX Shell Scripting