Job Description:
- Collaborate with stakeholders to develop a data strategy that meets enterprise needs and industry requirements.
- Create an inventory of the data necessary to build and implement a data architecture.
- Envision data pipelines and how data will flow through the data landscape.
- Evaluate current data management technologies and what additional tools are needed.
- Determine upgrades and improvements to current data architectures.
- Design, document, build and implement database architectures and applications. Should have hands-on experience in building high scale OLAP systems.
- Build data models for database structures, analytics, and use cases.
- Develop and enforce database development standards with solid DB/ Query optimizations capabilities.
- Integrate new systems and functions like security, performance, scalability, governance, reliability, and data recovery.
- Research new opportunities and create methods to acquire data.
- Develop measures that ensure data accuracy, integrity, and accessibility.
- Continually monitor, refine, and report data management system performance.
Required Qualifications and Skillset:
- Extensive knowledge of Azure, GCP clouds, and DataOps Data Eco-System (super strong in one of the two clouds and satisfactory in the other one)
- Hands-on expertise in systems like Snowflake, Synapse, SQL DW, BigQuery, and Cosmos DB. (Expertise in any 3 is a must)
- Azure Data Factory, Dataiku, Fivetran, Google Cloud Dataflow (Any 2)
- Hands-on experience in working with services/technologies like – Apache Airflow, Cloud Composer, Oozie, Azure Data Factory, and Cloud Data Fusion (Expertise in any 2 is required)
- Well-versed with Data services, integration, ingestion, ELT/ETL, Data Governance, Security, and Meta-driven Development.
- Expertise in RDBMS (relational database management system) – writing complex SQL logic, DB/Query optimization, Data Modelling, and managing high data volume for mission-critical applications.
- Strong grip on programming using Python and PySpark.
- Clear understanding of data best practices prevailing in the industry.
- Preference to candidates having Azure or GCP architect certification. (Either of the two would suffice)
- Strong networking and data security experience.
Awareness of the Following:
- Application development understanding (Full Stack)
- Experience on open-source tools like Kafka, Spark, Splunk, Superset, etc.
- Good understanding of Analytics Platform Landscape that includes AI/ML
- Experience in any Data Visualization tool like PowerBI / Tableau / Qlik /QuickSight etc.