Data Architect

This is a fully remote position, open to applicants in United States.

📋 Description

• Create and automate scalable data ingestion and transformation pipelines utilizing relational, event-driven, and unstructured data sources.

• Develop and sustain frameworks to monitor, identify, and address data quality and integrity concerns. Enforce data governance practices encompassing metadata management, data access, and retention policies.

• Design and oversee the development of reliable, efficient, and scalable ETL/ELT data pipelines equipped with monitoring and alerting mechanisms.

• Craft physical data models and enhance database structures, indexing, and relationships to improve performance.

• Test, refine, and troubleshoot data pipelines to guarantee stability and optimal performance.

• Create and manage large-scale data storage solutions using distributed and cloud platforms (such as data lakes, Hadoop, and NoSQL databases).

• Propel automation and modernization of data infrastructure and integration processes to facilitate agile analytics initiatives.

⛳️ Requirements

• A college degree, university degree, or equivalent in a relevant technical discipline, or equivalent relevant experience is mandatory.

• This role may necessitate licensing for compliance with export controls or sanctions regulations.

• Intermediate experience in a pertinent discipline area is required. Familiarity with the latest technologies and trends in data engineering is highly desirable, including:

• Understanding of complex business systems, industry requirements, and/or data regulations.

• Experience in processing and managing large datasets.

• Design and development experience for a Big Data platform utilizing open-source and third-party tools.

• Proficiency in SPARK, Scala/Java, Map-Reduce, Hive, Hbase, and Kafka or equivalent coursework.

• Knowledge of SQL query language.

• Experience with clustered compute cloud-based implementation.

• Background in developing applications that require significant file movement in a cloud environment, and other data extraction tools and methods from diverse sources.

• Experience in constructing analytical solutions.

• Intermediate experience in the following areas is preferred:

• Familiarity with IoT technology.

• Experience in Agile software development.

• Mastery of Dimensional Modeling — Extensive expertise in designing enterprise-scale dimensional models (star, snowflake, constellation) with a strong command of fact table grain definition, surrogate key strategies, slowly changing dimensions (Types 1–6), bridge tables, and handling late-arriving data.

• Advanced SQL Engineering — Highly skilled in crafting complex, high-performance SQL, including window functions, CTE-driven transformations, query plan analysis, cost-based optimization, partitioning strategies, and performance tuning across large, distributed datasets.

• Snowflake Architecture & Engineering — Practical experience with Snowflake internals including micro-partitioning, clustering keys, result-set caching layers, warehouse sizing/auto-suspend tuning, Snowpipe/Streams/Tasks orchestration, Time Travel, Zero-Copy Cloning, and secure data sharing patterns.

• Proficiency in Graph Database & Cypher — Strong experience with Neo4j or similar graph platforms, including graph schema design, Cypher query optimization, graph algorithms (PageRank, community detection, pathfinding), and integration of graph workloads with analytical and relational systems.

• Experience with Microsoft Fabric Ecosystem — Practical exposure to Fabric Lakehouse architecture, Delta Lake optimization, Data Engineering pipelines, Data Factory orchestration, KQL-based Real-Time Analytics, semantic model creation, and integration with Power BI and OneLake governance.

• Familiarity with SAP S/4HANA Data Structures — Understanding of SAP S/4HANA data models (FI/CO, MM, SD, PP), CDS views, OData services, SLT/SDI/ODP-based extraction patterns, and integration of SAP transactional data into cloud-based analytical platforms.

• Strong knowledge of Cloud Data Architecture — Proficient in distributed data processing, ELT/ETL orchestration, event-driven ingestion (Kafka/Event Hub), metadata-driven frameworks, schema evolution, and data lifecycle management across cloud environments (Azure preferred).

• Experience in Data Governance & Metadata Management — Skilled in implementing enterprise data catalogs, lineage tracking, data quality rules, master data integration, and security models (RBAC/ABAC, row-level and column-level security).

• Performance Engineering & Optimization — Capable of diagnosing bottlenecks across compute, storage, and network layers; optimizing workloads for cost and performance; and designing scalable, fault-tolerant data architectures.

• Cross-Platform Integration — Experience in integrating diverse systems (SAP, Snowflake, Fabric, graph databases, APIs, streaming platforms) into cohesive analytical ecosystems with a strong emphasis on interoperability and data consistency.

🏝️ Benefits

• Comprehensive health insurance plans.

• Flexible work hours and remote work options.

• Professional development opportunities and training programs.

• Competitive salary and performance-based incentives.