Associate Data Analyst

The Associate Data Analyst is responsible for collecting, analyzing and interpreting large and complex datasets to identify patterns and trends, surfacing facts and assist in developing insights and providing data-driven outputs and recommendations to support business decisions. The ideal candidate will have a keen interest in and some prior experience of data analysis, reporting and forecasting. The associate data analyst needs to be a clear communicator that can confidently interact with technical and non-technical stakeholders. The Associate Data Analyst will form part of and actively participate in the data analytics competency, with special focus on building data and reporting outputs as directed by senior team members. The analyst will be a contributing member of the analytics center of excellence (ACoE) and adopt best practices as outlined by ACoE leadership.

Responsibilities

Extract and analyze data from various sources including relational databases (mySQL, postgres), big data technologies (BigQuery, Kudu, Impala, SingleStore, Hive), file sources (parquet, ORC, avro, csv, xlsx) and reporting systems (Looker, DOMO); Assist with the identification, creation and maintenance of master datasets; Participate in data stewardship initiatives; Clean and manipulate data to ensure high quality and integrity of reporting outputs; Contribute to technical specifications for new data assets (marts, tables, views, cubes); Analyze source systems and help identify business logic embedded in the underlying datasets; Use statistical techniques to identify trends and derive patterns and insights embedded in the data; Identify and communicate data quality and data validation issues in productionalized datasets; Create visualizations and dashboards as directed by the squad lead and required by business stakeholders; Build and maintain dashboards and reports to support business stakeholders; Perform ad-hoc data analysis to determine suitability of a data source for use in data marts and reporting outputs or to assess key performance indicators (KPIs); Communicate findings and recommendations to both technical and non-technical team members in a clear and concise manner.

Requirements

Bachelor's degree in Mathematics, Statistics, Economics, Computer Science, or a related field; 2+ years of experience in a data analysis, business intelligence, or data engineering role; Strong Python and SQL coding skills; Demonstrable data analysis and data visualization skills; Hands-on exposure to data wrangling (data cleaning, manipulation, and preparation); Exposure to the Google Cloud Platform (GCP) and its integrated technologies; Familiarity with data visualization tools such as Tableau, Power BI, Looker, SSRS/SSAS, or QlikView; Strong analytical and problem-solving skills; Excellent verbal and written communication skills; Ability to work independently and collaboratively in a fast-paced, dynamic environment.

Nice to have

Deep exposure to DataBricks, PySpark, and BigQuery; Exposure to NoSQL data systems and streaming platforms (HBase, Redis, Kafka); Exposure to machine learning libraries, tools, and protocols (both supervised & unsupervised learning); Exposure to standard statistical modeling and forecasting methodologies; Prior experience working within the Marketing Technology (MarTech) industry.

Benefits

Responsible PTO policy; Up to 12 fully covered therapy/coaching sessions per year, with additional dependent coverage; Monthly gym reimbursement policy; Restricted Stock Units (RSUs) as part of total compensation with a 3-year vesting schedule; Free Coursera subscription and PXA courses; Parental leave policy: 26 weeks fully paid leave for primary caregiver and 13 weeks fully paid leave for secondary caregiver; Technology stipend for home office setup and monthly allowance for internet expenses.