Senior Data Analyst

We are seeking an experienced Senior Data Analyst with 8-10 years of expertise in data engineering, analytics, and insights generation. This role is critical in driving data-driven decisions across the organization, focusing on complex data problem-solving, designing efficient data systems, and delivering actionable insights.

As a Senior Data Analyst, you will work closely with cross-functional teams to transform data into strategic assets, ensuring data integrity, scalability, and usability.

Key Responsibilities

Data Sourcing & Ingestion

• Design and implement scalable and efficient data ingestion pipelines from multiple internal and external data sources.

• Develop and maintain data connectors, APIs, and streaming solutions to capture data in real-time or batch.

• Ensure data integrity and security during data acquisition processes.

Data Engineering & Storage

• Build and optimize ETL/ELT pipelines to transform raw data into structured, analysis-ready datasets.

• Design and manage data warehouses, data lakes, ensuring data scalability and availability.

• Implement data validation, cleansing, and transformation logic to maintain high data quality.

• Develop partitioning, indexing, and storage strategies to support high-performance querying and analytics.

Data Visualization & Insights Delivery

• Develop and deliver automated dashboards, reports, and data visualizations tailored to stakeholders’ needs using tools like Tableau, Power BI, Looker, metabase, superset.

• Collaborate with business teams to define and track key performance indicators (KPIs) and other critical metrics.

• Present complex data insights in a clear, actionable format for decision-makers.

Collaboration & Advisory

• Act as a trusted data advisor, collaborating with product, marketing, finance, and operations teams to align data strategies with business objectives.

• Mentor junior data engineers, analysts, or data professionals, fostering best practices and technical growth.

• Partner with technology teams to integrate data solutions into broader enterprise architecture.

Technology & Innovation

• Utilize modern big data technologies such as Apache Spark, Kafka, Apache Iceberg, or Dremio for scalable data processing and storage.

• Implement cloud-based data solutions (AWS, GCP, Azure) for data storage, processing, and analytics.

• Stay current with emerging data engineering tools, frameworks, and architectures to enhance capabilities and performance.

Qualifications

Education

• Bachelor’s degree in Computer Science, Data Analytics, Statistics, or a related field.

• Master’s degree is a plus.

Experience

• 8-10 years of experience in data analytics and data engineering roles.

• Proven track record of delivering impactful analytics solutions in complex, data-rich environments.

• Experience in managing and mentoring junior analysts or data professionals.

Skills

• Expertise in SQL, Python, or other analytical programming languages.

• Proficiency in data visualization tools especially Tableau, Power BI, or Looker.

• Strong knowledge of data warehousing concepts, ETL/ELT processes, and data modeling.

• Familiarity with cloud platforms (e.g., AWS, GCP, Azure).

• Excellent communication skills, with the ability to translate technical insights into business strategies.

• Strong problem-solving and critical-thinking skills.