We are seeking a highly skilled and analytical
Senior Data Analyst
with a strong background in Python, SQL, and modern data infrastructure. In this role, you will play a critical part in transforming raw data into meaningful insights that drive strategic decisions across the organization. You will work closely with product, engineering, and business teams to ensure that data is accessible, reliable, and actionable.
Key Responsibilities
- Write efficient and optimized
SQL queries
to support reporting and analytics. - Develop and maintain robust
Python
scripts and data pipelines for data transformation and automation. - Work with
PostgreSQL
and other OLAP databases to manage and query large datasets effectively. - Design, implement, and optimize dashboards and visualizations using
Metabase
, enabling self-service analytics across teams. - Understand and leverage
columnar file formats
(e.g., Parquet, ORC) and data compression techniques to improve storage and query performance. - Apply a solid understanding of
codec and compression algorithms
to analyze and troubleshoot data storage and performance bottlenecks. - Collaborate with data engineers and analysts to validate data models and maintain data integrity across reporting layers.
- Perform deep-dive analyses and generate actionable insights to improve business outcomes.
Qualifications & Skills
-
3+ years
of experience in a Data Analyst, BI, or similar role. - Proficiency in
Python
for data wrangling, scripting, and automation. - Strong hands-on expertise in
SQL
, including query optimization. - Experience working with
PostgreSQL
and at least one OLAP database
(e.g., ClickHouse, Redshift, BigQuery, Druid, etc.). - Understanding of
columnar storage formats
(Parquet, ORC, etc.) and when to use them. - Familiarity with
data codecs
and compression algorithms such as Snappy, Zstandard, LZ4, etc. - Deep, practical knowledge of
Metabase
: dashboard creation, advanced filtering, and embedding. - Strong analytical skills, with the ability to translate complex datasets into clear insights and recommendations.
- Excellent communication and stakeholder management skills.
Nice to Have
- Experience with modern data stacks or orchestration tools (e.g., dbt, Airflow).
- Exposure to data warehousing concepts and ETL/ELT frameworks.
- Familiarity with cloud-based analytics platforms (e.g., AWS, GCP, Azure)