Software Development Senior Analyst

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Date: Sep 2, 2026

Location: GDL, JAL, MX

Company: NTT DATA Services

Req ID: 387114 

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.

We are currently seeking a Software Development Senior Analyst to join our team in GDL, Jalisco (MX-JAL), Mexico (MX).

ROLE SUMMARY
Data engineer specialised in data virtualization with Denodo, responsible for designing, building and optimising the semantic layer that exposes governed data products to business consumers, BI tools and downstream applications. Integrates heterogeneous sources such as AWS, Oracle, Redshift and enterprise systems, combining virtualization with curated gold layer models under a medallion architecture, and is accountable for query performance and the responsiveness of the visualization layer. Works close to data governance and consumer teams, with proven delivery experience in enterprise or highly regulated environments.
REQUIRED TECHNICAL SKILLS
Denodo · Semantic Layer & Data Services (mid-expert level)
•    Logical modelling and layering: base views, derived views (join, union, selection, projection, aggregation, flatten) and interface views; disciplined separation between source, integration and business/semantic layers; naming conventions, reusability and version control of metadata.
•    Semantic layer for data products: business-friendly models, certified KPIs and metrics, association and hierarchy definition, field-level descriptions and business metadata so that consumers can self-serve without re-modelling.
•    Advanced SQL: complex queries, stored procedures, custom functions.
•    Query optimization (core requirement): cost-based optimizer, statistics management, query pushdown and delegation to Redshift/Oracle/S3, branch pruning, join strategy selection (merge, hash, nested), partitioned unions, and execution-trace analysis to diagnose and remediate slow queries.
•    Acceleration and caching: full, partial and incremental cache strategies, cache refresh scheduling and invalidation, summary views and smart query acceleration, and MPP acceleration over object storage.
•    Visualization performance: tuning of the consumption layer for Power BI, Tableau and similar tools: live vs. import trade-offs, aggregate awareness, result set reduction, concurrency and workload management to keep dashboard response times within agreed SLAs.
•    Publication and consumption: Data Catalog and Data Marketplace publication, tagging and categorization.
•    Security: role-based access control, row level and column level security, masking and data protection policies, and integration with LDAP/AD and SSO.
•    Operations: Design Studio, Solution Manager, Scheduler, promotion between environments (git export and import), monitoring of usage and workload, and diagnostics with logs and execution traces.
•    Server and environment management: installation and update of Denodo servers, virtual database and project structure, environment topology across Dev, QA and Production, and configuration of server properties and JVM memory settings. 
•    Metadata promotion and version control: VQL export and import, integration with Git for versioning of views and metadata, revision management, and rollback procedures for failed promotions. 
•    Data source administration: creation and maintenance of data source connections, driver deployment and upgrades, connection pool sizing, timeouts, and credential handling through the platform vault or an external secret store. 
•    Cache administration: configuration of the cache database, cache load and refresh policies, scheduling of maintenance jobs, purge of expired cache data, and sizing of the cache store. 
•    Scheduler: definition and operation of scheduled jobs for cache refresh, exports and extraction tasks, dependency configuration, and handling of job failures. 
•    Monitoring and diagnostics: use of the Diagnostic and Monitoring Tool, query and resource monitoring, analysis of server and query logs, identification of long running or blocking queries, and configuration of alerts and thresholds. 
•    Resource management: definition of resource plans and workload rules, concurrency and query limits by role or application, and protection of the server under peak load. 
•    Backup and continuity: backup of metadata and configuration, restore procedures, high availability and load balancing setup, and participation in disaster recovery testing. 
Data Sources & Integration
•    AWS: Redshift (SQL tuning, distribution and sort keys, WLM awareness), S3, Athena, Glue Data Catalog and Lake Formation as governed sources for virtualization.
•    Oracle: advanced SQL, PL/SQL reading ability, performance tuning, incremental extraction patterns and connectivity/driver configuration.
•    Other systems: SQL Server, flat and hierarchical files.
•    Federation vs. replication: criteria to decide when to virtualize, when to cache and when to materialise, based on volume, latency, concurrency and source impact.
Data Architecture & Modelling
•    Medallion architecture: clear understanding of bronze, silver and gold responsibilities, and where virtualization complements or replaces physical persistence at each stage.
•    Gold layer construction: dimensional and star-schema modelling, conformed dimensions, slowly changing dimensions, aggregates and business-rule implementation for consumption-ready models.
•    Data products: definition of data contracts, ownership, quality expectations, SLAs and versioning; documentation and lifecycle of published assets.
•    Working knowledge of Data Mesh and Lakehouse principles and of data governance practices (lineage, cataloguing, stewardship).
Complementary Tooling
•    Informatica: IDMC (Cloud Data Integration, Cloud Mass Ingestion) or PowerCenter, with mapping and taskflow development, pushdown optimization, and data quality rules feeding the curated layers.
•    AWS Glue: PySpark jobs, crawlers and Data Catalog management, and Glue workflows for ingestion and transformation into S3/Redshift.
•    Orchestration and DataOps: AWS Step Functions or equivalent schedulers, Git-based workflows, CI/CD pipelines, code review and environment promotion practices.
•    Python and SQL for automation, validation and data reconciliation.
KEY RESPONSIBILITIES
•    Design, build and maintain the Denodo semantic layer, translating business requirements into governed, reusable views and data products published to the Data Catalog and Data Marketplace.
•    Optimise query performance end to end through delegation, caching, summary views and model refactoring, so that reports and dashboards meet agreed response time targets.
•    Integrate new sources (AWS, Oracle, Redshift, APIs and enterprise systems) into the virtualization layer, defining connection, security and refresh strategies for each.
•    Build and evolve the gold layer: curated dimensional models, certified metrics and aggregates that serve as the single point of consumption for analytics teams.
•    Support the visualization teams as the technical counterpart for data access: model adjustments, aggregate design and troubleshooting of slow or failing reports.
•    Develop and maintain ingestion and transformation pipelines with Informatica and AWS Glue where physical processing is required upstream of the virtual layer.
•    Apply and document development standards, naming conventions, modelling patterns and promotion procedures across Dev/QA/Prod environments.
•    Provide L2/L3 support for the virtualization platform: incident analysis, root-cause investigation, cache and workload tuning, and continuous-improvement backlog.
•    Collaborate with data governance and security teams to enforce access policies, lineage capture and metadata quality on every published asset.
•    Contribute to technical estimation, solution design reviews and knowledge transfer to other engineers.
WAYS OF WORKING
•    Working proficiency in English  and Spanish (written and spoken).
CERTIFICATIONS (DESIRABLE)
•    Denodo Platform 9 Certified Developer Associate or Professional
•    Denodo Platform 9 Certified Administrator Associate or Professional.
•    Denodo Platform 9 Certified Architect Associate 

About NTT DATA

NTT DATA is a $30 billion business and technology services leader, serving 75% of the Fortune Global 100. We are committed to accelerating client success and positively impacting society through responsible innovation. We are one of the world's leading AI and digital infrastructure providers, with unmatched capabilities in enterprise-scale AI, cloud, security, connectivity, data centers and application services. our consulting and Industry solutions help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more than 50 countries. We also offer clients access to a robust ecosystem of innovation centers as well as established and start-up partners. NTT DATA is a part of NTT Group, which invests over $3 billion each year in R&D.

Whenever possible, we hire locally to NTT DATA offices or client sites. This ensures we can provide timely and effective support tailored to each client’s needs. While many positions offer remote or hybrid work options, these arrangements are subject to change based on client requirements. For employees near an NTT DATA office or client site, in-office attendance may be required for meetings or events, depending on business needs. At NTT DATA, we are committed to staying flexible and meeting the evolving needs of both our clients and employees. NTT DATA recruiters will never ask for payment or banking information and will only use @nttdata.com, @nttdatafed.com and @talent.nttdataservices.com email addresses. If you are requested to provide payment or disclose banking information, please submit a contact us form, https://us.nttdata.com/en/contact-us.

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