Data Architect (Managed Services)

The role

We are looking for a seasoned Data Architect with deep expertise in enterprise data warehousing, ETL/ELT pipeline development, and business intelligence. You will be responsible for the end-to-end design and implementation of our data architecture — from data ingestion and cleansing to dimensional modeling, warehouse construction, and BI dashboard delivery. You will also establish robust data governance frameworks including data catalogs, lineage tracking, and security audit systems.

What you need

Bachelor's degree or above in Computer Science, Statistics, Mathematics, Information Systems, or related technical field.
3+ years of professional experience in data development, data engineering, or data architecture roles, with a proven track record of building production data warehouse systems.
Expert-level proficiency in SQL (complex queries, window functions, CTEs, query optimization) and Python for data processing and pipeline development.
Mastery of data warehouse modeling theories and methodologies: dimensional modeling (Kimball), normalized modeling (Inmon), and Data Vault 2.0. Demonstrated experience designing star schemas, snowflake schemas, and aggregate tables for complex business domains.
Deep domain experience in at least one complex industry: financial services (banking, securities, insurance), international trade (import/export, supply chain, logistics), or manufacturing (production planning, quality control, industrial IoT). Understanding of industry-specific data entities, business processes, and analytical requirements.
Strong hands-on experience with ETL/ELT tools and frameworks: Apache Spark (batch and streaming), Apache Flink, Hive, MapReduce, Sqoop, DataX, SeaTunnel, or commercial ETL platforms (Informatica PowerCenter, Talend, IBM DataStage).
Proficiency in workflow orchestration: Apache Airflow, DolphinScheduler, Azkaban, Oozie, or equivalent scheduling and monitoring platforms.
Production experience with at least one major data warehouse/analytics database: ClickHouse, Apache Doris, StarRocks, Hive, Greenplum, Vertica, Teradata, or Snowflake.
Strong hands-on experience with BI and visualization tools: Apache Superset, FineBI, Tableau, Power BI, Quick BI, or similar enterprise BI platforms.
Deep expertise in Data Governance with demonstrated ability to build governance systems from scratch: data catalog implementation, metadata management, automated lineage tracking (using OpenLineage, Marquez, or similar), data quality monitoring, and security audit frameworks.
Solid understanding of relational and analytical databases: PostgreSQL, MySQL, Oracle, SQL Server, Greenplum — including performance tuning, indexing strategies, and query optimization.
Experience with big data ecosystem components: HDFS, YARN, ZooKeeper, Kafka, and Hadoop distributions (CDH, HDP, Apache).

Data Architect (Managed Services)

The role

Data Architect (Managed Services)

The role

What you need

Nice to have

Data Acquisition, Cleansing & Integration

Data Warehouse Architecture & Modeling

ETL/ELT Pipeline Development

Business Intelligence & Reporting

Data Governance & Standards

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Company facts

AvePoint