Data Modelling: Skilled in designing data warehouse schemas (e.g., star and snowflake schemas), with experience in fact and dimension tables, as well as normalization and denormalization techniques.
Data Warehousing & Storage Solutions: Proficient with platforms such as Snowflake, Amazon Redshift, Google BigQuery, and Azure Synapse Analytics.
ETL/ELT Processes: Expertise in ETL/ELT tools (e.g., Apache NiFi, Apache Airflow, Informatica, Talend, dbt) to facilitate data movement from source systems to the data warehouse.
SQL Proficiency: Advanced SQL skills for complex queries, indexing, and performance tuning.
Programming Skills: Strong in Python or Java for building custom data pipelines and handling advanced data transformations.
Data Integration: Experience with real-time data integration tools like Apache Kafka, Apache Spark, AWS Glue, Fivetran, and Stitch.
Data Pipeline Management: Familiar with workflow automation tools (e.g., Apache Airflow, Luigi) to orchestrate and monitor data pipelines.
APIs and Data Feeds: Knowledgeable in API-based integrations, especially for aggregating data from distributed sources.