# Data Management Analyst at Instant Impact

> Hybrid · Poland · Unspecified · Other · open. Source: https://alderhq.app/jobs/pinpoint%3Ainstant-impact%3A614869 (read 2026-11-06).

## Facts (observed)

- Company: [Instant Impact](https://alderhq.app/companies/instant-impact)
- Location text: Cracow, PL, Cracow
- Where it can be done from (inferred): Hybrid · Poland (evidence: "Location: Cracow, PL, Cracow")
- Posted: 2026-11-06 (0 days ago)
- First seen by alder: 2026-11-06 · last verified: 2026-11-06
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://careers.instant-impact.com/en/postings/20fe7af1-48b5-4942-be2f-05425432858c
- Skills listed (inferred): Python, Azure, SQL

## Pay and sponsorship

- Posted pay: not posted

## Description (the employer's text)

We are currently representing a leading global Financial Services firm in the appointment of high-calibre professionals as part of a period of strategic growth and investment.

Our client operates at the intersection of corporate, fiduciary and regulatory services, partnering with private equity houses, investment managers and international financial institutions. Backed by long-term institutional investment and an established global brand, the firm is scaling its capabilities, technology and international footprint.

Working as part of the Data team and reporting to the Data Management Lead, you will play a key role in improving data quality, strengthening metadata and lineage management, and supporting responsible data use across the organisation. You will work closely with Data Owners, Data Stewards, Data Engineering teams, and business stakeholders to ensure data is transparent, compliant, and ready to support analytics, automation, and future AI initiatives.

This is an excellent opportunity for a data professional who enjoys solving complex data challenges while helping to establish best practice within a developing data environment.

### Responsibilities

- Deliver data quality and data governance initiatives, including data profiling, validation, reconciliation, and root-cause analysis across structured and unstructured datasets.
- Identify and document Critical Data Elements (CDEs), including definitions, ownership, business rules, and authoritative sources.
- Develop and maintain data quality rules, controls, and thresholds using enterprise data quality tooling.
- Define and monitor data quality metrics, supporting remediation activities and continuous improvement plans.
- Work with Data Stewards and business stakeholders to resolve data quality issues and strengthen data controls.
- Maintain and enhance the enterprise data catalogue, ensuring data assets are accurately documented and easily discoverable.
- Implement and manage metadata standards, including classification, lineage, taxonomies, ownership, and usage guidance.
- Develop and maintain business glossaries and ensure metadata remains accurate and aligned to regulatory requirements.
- Promote data catalogue adoption and increase metadata awareness across business functions.
- Partner with Data Engineering teams to embed data quality controls and metadata capture into automated pipelines.
- Support lineage capture and transparency across data platforms and data flows.
- Contribute to governance forums, working groups, and data management initiatives.
- Recommend improvements to data handling, control frameworks, and operational processes.
- Support AI readiness by ensuring data assets are well-documented, controlled, and of high quality.
### Skills

- Proven experience in data quality, metadata management, data governance, or a related data management discipline.
- Hands-on experience with data quality and data catalogue tools, including profiling, rule management, lineage capture, glossary management, and metadata enrichment.
- Strong understanding of metadata concepts, including classification, lineage, taxonomies, ontology modelling, and business glossary management.
- Strong SQL and Python skills for data analysis, profiling, reconciliation, and control development.
- Understanding of modern cloud-based data platforms, particularly Azure and associated data architectures.
- Experience working with both structured and unstructured datasets.
- Knowledge of data lifecycle management, authoritative data sources, and data control frameworks.
- Ability to analyse complex data issues and translate findings into practical improvement actions.
- Strong communication and stakeholder management skills.
- Excellent attention to detail and organisational skills.
- Comfortable working in a growing or evolving data environment and helping shape processes, standards, and controls.

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/pinpoint%3Ainstant-impact%3A614869 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.