Competencies
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.
Requirement -
- Qualification: B.E/B.Tech/M.E/M.Tech/PhD from tier 1 Engineering institutes with relevant work experience with a top technology company.
- 3+ years of Backend and Infrastructure Experience with a strong track record in development, architecture and design.
- Hands-on experience with large-scale databases, high-scale messaging systems and real-time Job Queues.
- Experience navigating and understanding large scale systems and complex code-bases, and architectural patterns.
- Proven experience in building high-scale data platforms.
- Strong expertise in data warehouse schema design (star schema, fact tables, dimensions).
- Experience with data movement, transformation, and integration tools for data propagation across systems.
- Ability to evaluate and implement best practices in data architecture for scalable solutions.