MDM Data Engineer

MDM Data Engineer

• Location: Remote (Offshore)

• Job type: Full time

• Must Have Skills:

SKills

Rating out of 5

No of years exp

Snowflake- 5 Years

PL/SQL- 5 Years

Master Data Management- 5 Years

Scripting – Python- 5 Years

SAP/Salesforce/Engage to Graph DB- 5 Years

DBT- 5 Years

• Minimum IT Experience: 8+ Years

Role Summary

The MDM Data Engineer will build and operate the data pipelines, models, and profiling capabilities that power enterprise Master Data Management program. The engineer will work across the RAW / STAGED / PROFILE three-layer architecture, ingest data from authoritative source systems (SAP, Salesforce/Engage, and others), and contribute to the graph-based MDM model spanning Clubs, Schools, Colleges, and Individuals, along with the parallel Product MDM Style/Variant model. This is an offshore position operating in close collaboration with the data architecture and platform teams.

Required Skills

• Strong hands-on experience building data pipelines and models on Snowflake, including warehouse sizing, resource monitors, RBAC, streams/tasks, and cost-aware query design.
• Advanced SQL skills, including window functions, recursive CTEs, complex joins, MERGE patterns, and query performance tuning against large datasets.
• Strong Python development experience for data engineering — building ingestion jobs, transformation logic, reusable libraries, and automation scripts.
• Experience implementing and operating layered data architectures (e.g., RAW / STAGED / CURATED or Bronze / Silver / Gold), including landing-zone design, standardization, deduplication, and publication layers.
• Practical experience with data profiling and data quality — column-level statistics, pattern detection, uniqueness/nullability analysis, and rule-based validation. Profiling logic must be implemented in a database-agnostic manner (portable SQL and Python), not tied to Snowflake-specific features.
• Experience integrating with SAP as a source system, including familiarity with SAP master data structures (customer, material, vendor, pricing) and common extraction patterns (IDoc, BAPI/RFC, CDS views, or table-based extracts via ETL/replication tools).
• Experience implementing Master Data Management concepts: match/merge, survivorship rules, golden-record construction, cross-reference (xref) tables, and hierarchy management.
• Solid data modeling skills across relational, dimensional, and graph/network models, including entity–relationship design, slowly changing dimensions, and node/edge schemas.
• Experience applying DevOps practices — Git-based development workflows, pull requests, code reviews, CI/CD pipelines, and automated deployments for data code (DDL, DML, dbt/SQL projects, Python packages).
• Strong automation mindset with experience eliminating manual data-ops activities through scripting (Python, PowerShell, or Bash) and orchestration tools (Airflow, dbt, Snowflake Tasks, or equivalent).
• Experience working within Agile engineering teams using modern software delivery practices, story decomposition, and iterative delivery.
• Excellent troubleshooting, analytical, and problem-solving skills, particularly with data reconciliation, root-cause analysis of quality issues, and lineage tracing.
• Strong written and verbal communication skills, with the ability to collaborate effectively across time zones with data architects, business analysts, and platform engineering teams.
• Demonstrated willingness to learn new technologies and expand responsibilities beyond traditional data engineering (e.g., graph modeling, MDM tooling, AI/ML-assisted matching).

Preferred Skills

• Experience with Snowflake Cortex AI functions (embeddings, vector search, LLM-based classification) applied to entity resolution or attribute normalization.
• Experience with graph databases or graph data modeling (Neo4j, AWS Neptune, TigerGraph, or graph structures modeled on relational/columnar stores) for identity resolution and hierarchy traversal.
• Experience with commercial MDM platforms (Reltio, Informatica MDM, Semarchy, Profisee, Ataccama) or DQ tooling (Great Expectations, Ataccama DQ, Informatica IDQ).
• Experience with dbt for transformation, testing, documentation, and lineage.
• Experience integrating Salesforce data (Sales Cloud, Service Cloud, Marketing Cloud, or Loyalty/Engage) into an enterprise MDM.
• Familiarity with product master data concepts — style/variant modeling, attribute governance, classification hierarchies, and vendor-agnostic product structures.
• Exposure to AWS services relevant to data platforms (S3, Glue, Lambda, IAM, Secrets Manager) and Infrastructure as Code with Terraform.
• Experience with data cataloging, lineage, and governance tooling (Atlan, Collibra, Alation, Snowflake Horizon, OpenMetadata).
• Experience supporting business-facing data stewardship workflows, exception queues, and human-in-the-loop review processes.

Team Composition Requirements

The assigned offshore team shall consist of two (2) MDM Data Engineers with complementary technical expertise, working under the direction of the data architecture lead.

• Both engineers shall possess strong Snowflake and Python data engineering experience.
• At least (1) engineer shall possess senior-level MDM experience — hands-on match/merge, survivorship, hierarchy management, and golden-record delivery on a prior enterprise MDM program.
• At least (1) engineer shall possess strong SAP source-system integration experience for customer and/or material master data.
• Experience with graph modeling, Snowflake Cortex AI, and Salesforce integration is highly desirable across the team but is not required for both resources.
• The combined team should provide broad coverage across data engineering, data modeling, data quality/profiling, and MDM domain delivery.

Delta

is emerging as of the fastest growing

IT Staffing and professional services company

specializing in

SAP, Guidewire, Cloud, AI, ML, SRE, data and applications development

.

Headquartered

in

Texas

, we are a global company with

offices in USA, Canada, India, Europe, Middle East, Australia

. We help clients transform through business and technology consulting, digital solutions, applications development, maintenance and support services. Visit www.deltassi.com to learn more.

Delta is an equal opportunity employer and considers all applicants without regarding to race, color, religion, citizenship, national origin, ancestry, age, sex, sexual orientation, gender identity, or any other characteristic protected by law. We are committed to creating a diverse and inclusive environment for all employees.

• Snowflake: 5 years experience
• PL/SQL: 5 years experience
• Master Data Management: 5 years experience
• Scripting with Python: 5 years experience
• SAP/Salesforce/Engage to Graph DB: 5 years experience
• dbt: 5 years experience
• Minimum 8+ years IT experience
• Hands-on data pipelines and models on Snowflake (warehouse sizing, resource monitors, RBAC, streams/tasks, cost-aware query design)
• Advanced SQL: window functions, recursive CTEs, complex joins, MERGE patterns, query performance tuning
• Strong Python development for data engineering (ingestion jobs, transformation logic, reusable libraries, automation)
• Experience with layered data architectures (RAW/STAGED/CURATED or Bronze/Silver/Gold), landing-zone design, standardization, dedup, publication
• Data profiling and data quality: column statistics, pattern detection, uniqueness/nullability analysis, rule-based validation, database-agnostic implementation
• SAP source integration: master data structures (customer, material, vendor, pricing) and extraction patterns (IDoc, BAPI/RFC, CDS views, table extracts)
• MDM concepts: match/merge, survivorship rules, golden-record construction, xref tables, hierarchy management
• Data modeling across relational, dimensional, and graph/network models (ER design, SCDs, node/edge schemas)
• DevOps practices: Git workflows, pull requests, code reviews, CI/CD, automated deployments for data code
• Automation mindset: scripting (Python, PowerShell, Bash) and orchestration (Airflow, dbt, Snowflake Tasks)
• Experience working in Agile engineering teams with story decomposition and iterative delivery
• Strong troubleshooting, analytical, and problem-solving skills (data reconciliation, root-cause analysis, lineage tracing)
• Strong written and verbal communication; collaborate across time zones with teams
• Willingness to learn new technologies beyond traditional data engineering (graph modeling, MDM tooling, AI/ML-assisted matching)
• Snowflake Cortex AI functions (embeddings, vector search, LLM classification) for entity resolution or normalization
• Graph databases or graph data modeling (Neo4j, AWS Neptune, TigerGraph) for identity resolution and hierarchy traversal
• Commercial MDM platforms (Reltio, Informatica MDM, Semarchy, Profisee, Ataccama) or DQ tooling (Great Expectations, Informatica IDQ)
• Experience with dbt for transformation, testing, documentation, and lineage
• Integrating Salesforce data (Sales/Service/Marketing Cloud, Loyalty/Engage) into enterprise MDM
• Product master data concepts: style/variant modeling, attribute governance, classification hierarchies
• AWS data platform services (S3, Glue, Lambda, IAM, Secrets Manager) and Infrastructure as Code with Terraform
• Data cataloging, lineage, and governance tooling (Atlan, Collibra, Alation, Snowflake Horizon, OpenMetadata)
• Supporting data stewardship workflows, exception queues, and human-in-the-loop review processes