Purpose:

The Data Quality Assurance Officer will play a critical role in sustaining the reliability and continuity of all CRSDP’s data systems at a time when existing IM capacity is overstretched due to APSSF responsibilities and system development for the SCALE project. With large volumes of multi-district field data being generated, this position will ensure that all datasets are accurately compiled, systematically cleaned, validated, securely stored, and readily usable for technical planning and analysis. The role will also strengthen day-to-day coordination with district-level DQAs and engineering teams, reduce the current backlog in data processing, and maintain consistent dashboard updates and reporting. By providing dedicated data management and quality oversight, the DQA Officer will help safeguard the integrity of CRSDP evidence and ensure timely, high-quality inputs for settlement planning, decision-making, and partner coordination.

Project Background

The Sindh Peoples Housing for Flood Affectees (SPHF) is a Government of Sindh entity mandated to lead the reconstruction of 2.1 million flood-affected houses across the province, with a strong focus on resilience, sustainability, and risk-informed recovery.

To support evidence-based planning at the settlement level, SPHF, in collaboration with Catholic Relief Services (CRS), is implementing the Climate Resilient Settlement Development Plan (CRSDP) across seven districts of Sindh. The CRSDP aims to generate integrated, data-driven settlement plans that address housing, WASH, infrastructure, climate risks, and long-term operations and maintenance.

The initiative involves large-scale field data collection and technical assessments, carried out by a multidisciplinary team comprising Data Enumerators, Engineers, Field Monitors, and Data Quality Assurance (DQA) staff. High-quality, accurate, and well-organized data is critical to inform technical designs, planning decisions, and coordination with government and development partners.

Objectives and Responsibilities

The Data Quality Assurance (DQA) role based in Karachi will play a central function in ensuring the reliability, consistency, and usability of field data through systematic review, cleaning, validation, and close coordination with field teams. This consultancy will involve collaborating closely with field teams to compile, clean, and validate data to meet project requirements and quality standards.

The DQA Officer will provide services covering data intake, validation, cleaning, repository management, dashboard refreshes, training, and continuous quality improvement aligned to CRSDP protocols and SPHF/CRS standards.

The position will be responsible for below mentioned tasks:

• Coordinate directly with field teams to receive daily/weekly data submissions from all districts and clarify any gaps at source.
• Maintain a centralized, well-structured data repository (by district, village, date, and tool) to support easy tracking and analysis.
• Review incoming data for completeness and obvious errors (missing fields, duplicates, outliers) before moving to detailed cleaning.
• Apply clear data-cleaning steps (error correction, consistency checks, handling missing values) using agreed protocols and formats. Document all transformations in a DQA log and retain original raw data.)
• Use practical tools (Excel, Google Sheets, Kobo exports, or other agreed software) to clean and manage data efficiently.
• Flag data inconsistencies and follow up with field teams immediately for verification or correction. Track query resolution in a data issue log, with timestamps and responsible persons.
• Conduct quality checks on cleaned datasets to ensure alignment with survey tools, indicators, and project standards.
• Validate data by cross-checking with original forms, photos, GPS points, or reference datasets where required.
• Document key data issues, corrections made, and lessons learned in short quality summary notes or logs. Produce a weekly DQA summary report consolidating issues, resolutions, and recommendations.)
• Maintain regular communication with field teams to understand data collection challenges and adjust processes accordingly. Facilitate a weekly coordination meeting with MEAL/IM teams.
• Support and orient field staff on correct data entry, common errors, and basic quality checks based on recurring issues.
• .Implement a structured continuous improvement plan with agreed corrective actions, ownership, and timelines.

Tools & Platforms

• Primary: Kobo/CommCare, Microsoft Excel, Google Sheets, Power BI, Google Drive/SharePoint.
• Optional: basic GIS tools for GPS validation (e.g., QGIS), and standard QA/QC scripts/macros where applicable.

Deliverables

• Submit a brief daily progress report summarizing data received, districts covered, cleaning status, key issues identified, and actions taken.

• Ensure daily data refreshes where new data exists and deliver weekly dashboard enhancements/bug fixes, with documented change logs.

• Clearly organized Google Drive folder structure (by district, village, date, and data type) that allows easy review, tracking, and analysis by the project team.

• Deliver cleaned datasets with errors, inconsistencies, and missing values identified, corrected, or clearly flagged with explanations.

• Document and report data-related challenges (collection gaps, tool issues, field constraints) along with recommended corrective actions. Maintain a risk & issue register and update weekly

 Completion Milestones:

a)    Attend the orientation session prior to the field work.

b)    Compiled and organized data sets from field activities.

c)     Cleaned data sets free of errors, inconsistencies, and missing values.

d)    Quality assurance reports highlighting data accuracy and integrity.

e)    Orientation materials and support provided to field teams on data quality assurance processes.

f)      Report any challenges encountered during data compilation, cleaning and validation process.

Reporting relationships

The Data Quality Assurance Officer will report and work closely with field based DQA teams and Engineer and Program Manager. They will also have working relationships with the MEAL Advisor and Information Management Officer. During the assignment, organization will provide transport to/from field, when needed. Primary reporting line to the Program Manager (CRSDP); functional reporting to MEAL Advisor and Information Management Officer. Weekly coordination meetings required; monthly performance review aligned to KPIs.)

Duration of contract

Contract duration for the assignment will be 03 months. Initial term of three (3) months, with possibility of extension subject to performance, project needs, and funding.

Required Competencies, Experience and Qualification

Personal Qualities

• Must be reliable and committed to fulfilling assignments with high level of professionalism.
• Must be able to work independently as well as within a team environment.
• Ability and willingness to work long hours and sometimes in adverse field conditions.
• Demonstrates proactive problem-solving and sound judgment under time constraints
• Highly punctual, organized, and flexible.
• Demonstrates proactive problem-solving and sound judgment under time constraints. Adheres to professional conduct, safeguarding, and code of ethics
• Must be able to assure confidentiality of respondents’ personal information/data collected from field areas.
• Proficiency in English required; Sindhi and/or Urdu preferred.)

Education

• Bachelor’s degree in computer science, Data Science, Statistics, Engineering, or related field; relevant diplomas/short courses in data management/analysis are an asset.

Experience

• Previous experience in data compilation, cleaning and validation. Minimum 2–3 years preferred in data quality roles
• Hands-on experience with Kobo Toolbox and/or CommCare, including form schema exports and validation .
• Familiarity with Microsoft Office. Advanced Excel skills (lookups, pivot tables, data validation, Power Query); Power BI experience for data quality monitoring
• Demonstrated data analysis and visualization skills using Excel and Power BI; basic GIS (QGIS) for GPS validation is an advantage. .
• Proven ability to implement DQA protocols, maintain audit trails, and collaborate with MEAL/IM teams.

Data Governance, Security & Confidentiality (Added)

• Comply with SPHF/CRS data protection policies, consent protocols, and applicable laws/regulations.
• Protect personally identifiable information (PII); restrict access on a need-to-know basis; no unauthorized data sharing.
• Maintain audit trails; preserve raw data; document transformations; use secure storage (Google Drive/SharePoint with controlled permissions).
• Adhere to ethical standards and safeguarding principles in all data handling.

Sign-off

• This SOW becomes effective upon signature by the DQA Officer and the authorized representative(s) of SPHF/CRS. Changes require written agreement.