Data Analyst job description

Data and analytics — Data Analyst
Owns analyses and reporting for a domain with little oversight.

RESPONSIBILITIES
- Build pipelines that handle late-arriving and out-of-order data, backfill history safely, and keep runs idempotent.
- Write efficient queries against large tables, choosing indexes and query shape to avoid a full scan, and explain a query plan to a colleague.
- Add a new dimension attribute or a straightforward fact table to an existing model, following the conventions already in place.
- Write a transformation step that joins and reshapes several sources into one model, documenting the assumptions you made.
- Add a table to the correct layer, following existing partitioning and naming conventions.
- Design the checks and alert thresholds for a new dataset so they catch silent failures, and root-cause a recurring failure to its source system.

REQUIREMENTS
- Experience at the Junior Data Analyst level (level 1 of 5) or equivalent
- Holds Salesforce Certified Tableau Desktop Foundations

REQUIRED SKILLS
Data Engineering
- Analytical SQL Querying — You can write efficient queries against large tables, choosing indexes and query shape to avoid a full scan, and explain a query plan to a colleague.
- Dimensional Data Modeling — You can add a new dimension attribute or a straightforward fact table to an existing model, following the conventions already in place.
- Data Pipeline Development — You can build pipelines that handle late-arriving and out-of-order data, backfill history safely, and keep runs idempotent.
- ETL/ELT Transformation Design — You can write a transformation step that joins and reshapes several sources into one model, documenting the assumptions you made.
- Data Warehouse Architecture — You can add a table to the correct layer, following existing partitioning and naming conventions.

Data Governance
- Data Quality and Pipeline Monitoring — You can design the checks and alert thresholds for a new dataset so they catch silent failures, and root-cause a recurring failure to its source system.
- Metric Definition and Governance — You can write a clear definition for a new, uncontested metric, including its calculation and known edge cases.
- Data Lineage and Documentation — You can document the datasets you build to the standard the team expects and keep the lineage record current when you change a transformation. You do not leave the write-up until the end.
- Data Ethics and Privacy — You can design roles and retention for a dataset so it holds only what its purpose needs, and answer a subject access or deletion request against it.

Statistics & ML
- Statistical Analysis and Inference — You can run a standard hypothesis test or confidence interval for a straightforward comparison, and state what its result does and does not show.
- Experiment Design and A/B Testing — You can set up a straightforward A/B test with a clear hypothesis, a correctly sized sample and a pre-registered success metric.
- Predictive Modeling and Machine Learning — You can describe, in plain terms, the difference between a regression problem and a classification problem.
- Feature Engineering — You can create the standard features a model needs from clean fields and explain what each one represents. You check for leakage and missing values instead of assuming the raw data is fit to use.
- Forecasting and Trend Analysis — You can fit standard forecasting models to a clean series, handle seasonality, and report a range rather than a single number. You go back and check the forecast against the outcome.
- Data Exploration and Preparation — You can cleanse a familiar dataset by fixing formats and missing values, and record each change you made in a log.
- Programming for Analysis — You can write tested, documented Python or R analysis code that a colleague can rerun to get the same results.

Visualization
- Dashboard Design — You can design a dashboard for an ambiguous request by first working out what decision it needs to support, and cut features that do not serve that decision.
- Data Visualization Best Practice — You can choose a chart for a straightforward comparison that avoids distortions such as a truncated axis, and pick colors that readers with color-blindness can tell apart.
- Stakeholder Analytics Translation — You can challenge a stakeholder's framing and agree a written problem statement that names the decision to be made and how the analysis will inform it.
- Analytics Storytelling and Reporting — You can present a result to a non-technical colleague, explaining what it means and how confident you are, without walking them through the query. You answer the follow-up rather than repeating the chart.

Delivery
- Project Management — You can organize a small piece of work into steps, put them in a sensible order, and finish it by the date you agreed, raising problems before they cause a delay.
- Planning & Estimation — You can estimate your own work with reasonable accuracy and keep a steady enough pace that other people can plan around you.
- Ownership & Accountability — You can pick up a problem that has no obvious owner and make yourself accountable for it, including the parts nobody enjoys.
- Quality Focus — You can define what good enough means for a project, put checks in place to show it has been met, and hold work back when it falls short.

Craft
- Problem Solving — You can break a large, ambiguous problem into pieces and weigh the options for each against the evidence.
- Domain Expertise — You can work confidently with the tools and methods your team uses daily, and you can explain how your work serves the team's goals.
- Continuous Learning — You can pick up an unfamiliar area fast enough to be useful in it, and you turn what you learned into something others can reuse.

Communication
- Communication — You can explain a complex topic to people with very different backgrounds, adjusting the detail to the audience without talking down to them.
- Collaboration — You can build working relationships beyond your own team and get things done through people who do not report to you.
- Writing & Documentation — You can write for a defined audience, whether a proposal, a policy, a report, or a decision record, and make the reasoning as clear as the conclusion.
- Stakeholder Management — You can identify who is affected by your work and keep them updated at a level of detail and a frequency that suits them.

Leadership
- Leadership — You can spot a problem and propose a way forward unprompted, and you take a small leading role such as running a working group.
- Mentoring — You can help someone new settle into your team's work, answer their questions patiently, and give feedback specific enough to act on.
- Strategic Thinking — You can connect your team's work to its goals and question a task that does not appear to serve them.

REQUIRED CERTIFICATIONS
- Salesforce Certified Tableau Desktop Foundations (required from Data Analyst)