Project description

We are looking for a Data Architect to design and drive the implementation of a new Data Platform. You will define the target architecture, guide incremental delivery, and ensure the platform meets stringent requirements for scale, latency, and compliance.

Responsibilities

Define the end-to-end data architecture for a modern Data Platform that supports data unification, governance, analytics, and activation use cases.

Translate business requirements into target state architecture, reference models, and architectural decision records (ADRs).

Design scalable patterns for data ingestion, storage, modeling, processing, and serving, ensuring performance, resilience, and maintainability.

Drive an incremental delivery approach: prioritize high-value capabilities, deliver thin end-to-end slices, and scale based on feedback and measured outcomes.

Work closely with engineering, security, privacy, and product stakeholders to align architecture with enterprise standards and compliance requirements.

Define observability standards for pipelines and data services (monitoring, alerting, logging, dashboards) and contribute to incident prevention and root cause analysis.

Establish non-functional requirements and operational processes for reliable production operations (release strategy, rollback plans, runbooks).

Lead integration of data from multiple enterprise systems using a combination of batch and event-driven ingestion approaches.

Set up data quality controls (validation rules, anomaly detection, reconciliation, and monitoring) and ensure quality gates for new sources and transformations.

Establish governance practices, including metadata management, lineage, retention policies, access control patterns, and auditability.

Design and govern data access patterns for downstream consumers: curated datasets, semantic layers, and API-based access where required.

Ensure data products are well documented, versioned, and discoverable, with clear SLAs and operational ownership.

Partner with application teams to enable integration into business workflows and customer-facing experiences.

Skills

Must have

7+ years in Data Architecture/Enterprise Data Platforms.

Strong knowledge of event-driven and batch ingestion patterns, data modeling, and history patterns.

Strong knowledge of Real-time/low-latency architecture concepts and SLAs.

Strong knowledge of governance (metadata, lineage, audit, access controls).

Demonstrated ability to design for hundreds of millions of records, multi-market complexity, and operational resilience.

Experience with Azure

Experience with Snowflake serving curated datasets and analytics workloads.

Experience with Databricks/Spark for heavy processing and advanced matching/ML where needed.

Experience with Data lake formats and layering (bronze/silver/gold).

Familiarity with streaming/event ingestion patterns and near-real-time propagation.

Strong communication skills to be able to align product, engineering, security, and stakeholders around architecture and trade-offs.

Native Spanish

English B2

Nice to have

Other

Languages

English: C1 Advanced,Spanish: C2 Proficient

Seniority

Senior

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