Data Analyst job description

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

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 Modelling — 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 Pipeline Monitoring and Alerting — You can add the agreed checks to the pipelines you build, and you follow the runbook when an alert fires. You escalate the alerts you cannot resolve rather than muting them.

Data Governance
- Data Quality Monitoring — You can design the quality checks for a new dataset, covering the failure modes that actually occur in it, 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 Privacy and Compliance — You can design a dataset or pipeline so it collects and retains only what its purpose requires, and answer a subject access or deletion request against it.
- Role-Based Data Access Control — You can apply the access rules the organisation has set, including masking or withholding sensitive columns, and you record what you granted to whom. You notice a request asking for more than the job needs.

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 Modelling Fundamentals — 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.

Visualisation
- 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 Visualisation Best Practice — You can pick a sensible chart for a straightforward comparison and avoid the common distortions, such as a truncated axis or a pie with ten slices. You fix a chart once told what is misleading about it.
- Exploratory Data Analysis — You can explore a familiar dataset and describe its shape, quality and obvious relationships. You check what a field really contains instead of trusting what its name suggests.
- Stakeholder Analytics Translation — You can push back on a stakeholder's framing when the question they asked is not the one that answers their actual problem, and get agreement on the real one.
- 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 break a small piece of work into tasks, sequence them, and run it to a date you agreed, escalating risks before they become slips.
- Planning & Estimation — You can estimate your own tasks with reasonable accuracy and deliver at 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 the accountable party for it, including the parts nobody enjoys.
- Quality Focus — You can define what good enough means for a project, put the checks in place to prove it, and hold back a release that misses the bar.

Craft
- Problem Solving — You can break a large, ambiguous problem into tractable pieces, weigh the options against evidence, and explain the tradeoff you chose.
- Domain Expertise — You can work confidently across the systems and tools 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.
- Technical Writing — You can write for a defined audience, whether a proposal, a runbook, 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 cadence that suits them.

Leadership
- Leadership — You can identify a problem and propose a way forward unprompted, and you take a small leading role such as running a working group.
- Mentoring — You can onboard someone onto 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)