Job Summary

The ideal candidate will turn data into actionable insights to aid business decisions, develop analytics solutions in line with client’s requirements, and design, implement, and maintain scalable and highly available data pipelines on large volume data sets, that will enable impactful insights & strategy for our product and services.

Key Responsibilities:

• Work closely with business lines, product, engineering, data science, and other data analytics teams to understand requirements/goals and provide viable and innovative data solutions.
• Develop analytical and statistical approaches to answer business questions, examine data validity, structure data, and provide insights into available data.
• Identify and set up performance-tracking dashboards and reports for internal and external stakeholders.
• Ensure that dashboard and reports continually maintain and improve in line with business realities.
• Create dashboards that help quickly detect problems with the product and services.
• Provide Support and training for dashboard usage.
• Identify and work with the data engineering team to incorporate 3rd party data assets to augment internal data.
• Contribute improvements and advancements in our data warehouse/data lake, company-level business intelligence reports, and training regimens for business analysts on other teams.
• Effectively plan tasks across multiple projects simultaneously with different requirements, needs, and priorities.
• Mentor team members and provide leadership.
• Translate business requirements by the business team into data engineering specifications.
• Ensure all company data is available and accessible in a central location.
• Build scalable data marts from the available raw data that can be used to derive business metrics/insights as specified by stakeholders.
• Work hand in hand with the DevOps team and develop monitoring and alerting scripts on various data pipelines and jobs.
• Process, clean, and validate the integrity of data to be used for analytics purposes.
• Work with engineering and product teams to ensure that products are designed to properly capture required data fields.
• Expand and optimize data and data pipeline architecture.
• Collaborate with data analyst teams to incorporate 3rd party data assets to augment internal data.
• Effectively plan tasks across multiple projects simultaneously with different requirements, needs, and priorities.
• Provide Support and training for data usage.
• Mentor team members and provide leadership.

Academic Qualification(s)

• Good first degree in Computer Science/ Statistics/related field

Experience

• Minimum of 5 years in a Data Analytics or Data Engineering role with 1 year in a number crunching role for reporting purposes such as operations reporting, statistics, etc.
• Knowledge of data visualization tools (Excel, Tableau, Power BI), Machine Learning (regression, classification, clustering), Programming Language (SQL, Python/Scala), ETL & ELT tools (SSIS, Spark, Sqoop, Apache Airflow), Database Management (MS SQL, Mongo, Casandra, MaprDB- MaprFS), Cloud Services (AWS / Azure) and Realtime Data processing (Kafka)