Design and architect Data Warehouse, Data Lake, and Data Lakehouse solutions
to support enterprise-scale analytics and reporting needs.
Build, optimize, and monitor ETL/ELT pipelines (batch and streaming) to process
large volumes of data from multiple internal and external sources.
Integrate and manage data from diverse platforms, including databases, APIs, third-party
services such as PostgreSQL, Redis, and Snowflake.
Implement and maintain high-performance data storage and processing solutions
(Spark, Hadoop ecosystem, Snowflake, PostgreSQL).
Use Pandas and Python Dash to design analytical workflows and build interactive
dashboards for visualization and reporting.
Ensure data integrity, security, and compliance with industry standards and
regulations (GDPR, ISO 27001, SOC 2).
Optimize query performance and reduce infrastructure costs without compromising
data quality or reliability.
Provide clean, complete, and timely datasets to support
Data Analysts, Data
Scientists, and business stakeholders.
Propose and lead data infrastructure improvements for scalability, performance,
and cost optimization.
Collaborate with cross-functional teams to align data architecture with business
and product strategies.
Competitive salary.
Performance-based bonuses/ 13th month salary.
Comprehensive health, dental, and vision insurance plans.
Professional development and training programs.
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