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Seeka Technology

<div>Company Description 
We believe strong early career roles should do more than give someone a job title. They should help people grow into the kind of professionals they want to become. At SEEKA Technologies, we give junior team members meaningful work that builds real capability, sharpens problem-solving, and develops practical experience in fast-moving business and technology environments. Our goal is to help emerging talent strengthen their skills, expand their potential, and prepare for a future shaped by constant innovation across business and IT.
SEEKA Technologies (Not Seeka Limited) is a project under its parent organisation, called Fresh Futures Australia, which is an education consultant based in both Australia and Malaysia. We are developing and creating a platform that utilises A.I. to help match students and job seekers to the right opportunities relevant to them from Kindergarten up to the University, along with vocational training centres and language schools, and of course to businesses and companies who need the right candidates. Our mission is to make it easier for anyone to find, filter and apply to educational institutions and companies in a more seamless manner.
We are currently looking to hire a junior Backend AI &amp; Data Pipeline Engineer who wants to build real-world experience in backend systems, data processing, scraping, retrieval, and cloud-based infrastructure. This role is ideal for someone who already has hands-on technical experience and wants to grow further by working on meaningful engineering challenges that support Yuzee&rsquo;s intelligent matching platform. You will contribute to the systems that process data, power search and matching, and improve the efficiency, reliability, and scalability of our platform.
Below are the important details you will need to take note of:<ul><li>
English is the primary language used in the role</li><li>
This is a full-time remote/work-from-home position</li><li>
We welcome both local and international candidates</li><li>
Candidates should have a degree or proven practical experience relevant to the role</li></ul> 

Job Description 
About the role
We are looking for a Backend AI &amp; Data Pipeline Engineer to own the end-to-end data processing infrastructure that powers Yuzee's intelligent course and job matching platform. You will design and maintain scalable, event-driven pipelines that process tens of thousands of daily records, generate semantic embeddings, and feed a growing knowledge graph used for personalised career pathway recommendations.
What you'll do<ul><li>
Design and maintain three distinct processing pipelines &mdash; scheduled job ingestion, event-driven course processing, and a periodic knowledge graph builder &mdash; each with independent trigger logic and cost controls</li><li>
Generate and manage semantic embeddings via Amazon Bedrock (Titan v2), index them in MongoDB Atlas Vector Search, and calibrate similarity thresholds to ensure match accuracy</li><li>
Build and maintain a knowledge graph linking jobs, courses, skills, and industries using FP-Growth association rules and archetype-to-SOC code mapping</li><li>
Build and improve a two-stage discovery and matching API on AWS Lambda &mdash; vector retrieval first, then deep eligibility scoring with LLM re-ranking</li><li>
Right-size Fargate Spot instances and design resumable processing loops that tolerate interruption, keeping infrastructure costs under control as data volume scales</li><li>
Maintain and improve daily job scrapers across multiple sources and build institution data scrapers with robust HTML cleaning pipelines</li></ul>
What we're looking for<ul><li>
1+ years of backend engineering experience focused on data pipelines, ML infrastructure, or search systems</li><li>
Hands-on experience with AWS serverless and container services &mdash; Lambda, ECS Fargate, EventBridge, and Step Functions</li><li>
Strong Python skills &mdash; Pandas, async processing, bulk database operations, and text cleaning</li><li>
Familiarity with vector databases and semantic similarity search; MongoDB Atlas Vector Search experience is a strong plus</li><li>
Cost-conscious infrastructure mindset &mdash; you think in per-record compute costs, free tiers, Spot resilience, and right-sizing</li><li>
Ability to document and communicate complex architecture clearly to both technical and non-technical stakeholders</li></ul>
Nice to have<ul><li>
Experience with knowledge graphs or association rule mining (FP-Growth, Apriori)</li><li>
Experience using LLMs for re-ranking or eligibility assessment on top of vector retrieval results</li><li>
Background in edtech, jobtech, or recommendation/matching systems</li></ul> 

Qualifications 
Degree or existing proven experience 
Additional Information 
Use this instead:
Benefits<ul><li>
Fully remote / work-from-home role</li><li>
Flexible working hours within the team&rsquo;s expected schedule and business needs</li><li>
Opportunity to work on real backend, data, and AI infrastructure projects</li><li>
Exposure to practical engineering challenges in scraping, pipelines, retrieval, and cloud systems</li><li>
Ongoing growth and development within a fast-moving technology environment</li><li>
Opportunity to build long-term value and grow with the company based on performance, including progression and increased responsibility over time</li></ul>
A slightly more polished version:
Benefits<ul><li>
Fully remote / work-from-home position</li><li>
Some flexibility in working hours, depending on team requirements and deliverables</li><li>
Hands-on experience working on meaningful backend, data pipeline, and AI-related systems</li><li>
Opportunity to contribute to a growing platform with real product and engineering challenges</li><li>
Professional growth in a practical, fast-paced environment</li><li>
Strong potential for long-term progression based on performance, regardless of location</li></ul>
If you want it to sound more attractive for hiring, the strongest version would be to add things like:<ul><li>
ownership</li><li>
real product impact</li><li>
career growth</li><li>
direct exposure to architecture and scaling decisions</li></ul></div>

Backend AI & Data Pipeline Engineer

International Rescue Committee

<div>The International Rescue Committee (IRC) responds to the world's worst humanitarian crises, helping to restore health, safety, education, economic wellbeing, and power to people devastated by conflict and disaster. Founded in 1933 at the call of Albert Einstein, the IRC is one of the world's largest international humanitarian non-governmental organizations (INGO), at work in more than 40 countries and 29 U.S. cities helping people to survive, reclaim control of their future and strengthen their communities. A force for humanity, IRC employees deliver lasting impact by restoring safety, dignity and hope to millions. If you're a solutions-driven, passionate change-maker, come join us in positively impacting the lives of millions of people world-wide for a better future.
Technology and Operations support the organization's work by providing reliable and scalable solutions for the IRC's offices around the world. The Data Team at IRC is responsible for the design and delivery of global data strategies and the systems and products that deliver on it. 
Job Overview / Summary 
The Data Engineer will support the implementation, configuration, and maintenance of data pipelines and transformation workflows across IRC's data environment. This role plays an active part in building and operating ELT processes, dbt models, and cloud-based data platforms including Azure Databricks and the IRC Lakehouse. 
The successful candidate has foundational to growing expertise in dbt, SQL, and Databricks, and is eager to take on increasing ownership of data engineering deliverables. Working closely with senior engineers and the Data Architect, this role contributes to data modeling, pipeline development, and platform reliability in a collaborative and fast-paced environment. 
Major Responsibilities<div> 
Pipeline Engineering &amp; Orchestration 
<ul><li>Build and maintain ELT data pipelines using Databricks Workflows and Azure Data Factory for batch and scheduled processing from internal and external sources.</li><li>Support the ingestion of data from key systems (e.g., D365 CRM, ServiceNow) into Lakehouse.</li><li>Monitor pipeline execution, identify failures, and troubleshooting issues in collaboration with senior engineers.</li><li>Contribute to pipeline documentation and help maintain runbooks and process standards.</li></ul></div><div> 
dbt Development 
<ul><li>Develop and maintain dbt models across staging, intermediate, and mart layers under the guidance of senior team members.</li><li>Write dbt tests and contribute to source freshness checks to support data quality.</li><li>Learn and apply dbt best practices including modular design, ref dependencies, and incremental model patterns.</li><li>Work with analysts and business teams to translate data requirements into dbt models.</li></ul></div><div> 
SQL &amp; Data Transformation 
<ul><li>Write intermediate to advanced SQL for data extraction, transformation, and validation tasks.</li><li>Apply SQL techniques including joins, CTEs, window functions, and aggregations to support reporting and analytics needs.</li><li>Assist in query optimization and performance troubleshooting within</li></ul></div><div>
Databricks SQL environments. 
<ul><li>Support data model maintenance and help accommodate new source fields or schema changes.</li></ul></div><div> 
Databricks &amp; Cloud Platform 
<ul><li>Develop and maintain Databricks notebooks and jobs for data transformation workloads.</li><li>Gain hands-on experience with Delta Lake concepts and PySpark for data processing.</li><li>Follow Lakehouse design patterns (Bronze/Silver/Gold) as defined by the Data Architect.</li><li>Support cloud resource management including basic cluster configuration and job scheduling.</li></ul></div><div> 
Collaboration &amp; Learning 
<ul><li>Actively collaborate with the Data Team on pipeline design, troubleshooting, and delivery.</li><li>Participate in code reviews and incorporate feedback to improve code quality.</li><li>Support documentation of processes, standards, and data flows.</li><li>Engage with Finance, FP&amp;A, and other business teams to understand data needs and assist in solution delivery.</li></ul></div><div> 
Key Working Relationships 
<ul><li>Data Team (Data Architect, Lead Data Engineer, Data Analysts)</li><li>Business / Departmental Priority Setters (Finance, FP&amp;A, Operations)</li><li>Enterprise Systems Owners (D365 CRM, Integra)</li></ul>
Position Reports To</div> 
Lead Data Engineer 
Position Supervises: None 
Travel Requirements 
Special projects may require travel to enable on-the-ground learning to support data strategy deliverables. 
Minimum Requirements<div> 
Experience 
<ul><li>3&ndash;6 years of hands-on experience in data engineering, analytics engineering, or a related technical role.</li><li>Demonstrated experience building or maintaining data pipelines in a professional setting.</li><li>Exposure to cloud-based data platforms, preferably Azure (Databricks, Data Factory, or Synapse).</li></ul></div><div> 
Technical Skills &mdash; Required 
dbt: 
<ul><li>Working knowledge of dbt model development including staging and mart layers.</li><li>Familiarity with dbt tests, documentation, and source configurations.</li><li>Eagerness to deepen dbt skills including incremental models and CI/CD integration.</li></ul></div><div> 
Databricks: 
<ul><li>Hands-on experience with Databricks notebooks and basic job/workflow setup.</li><li>Familiarity with Delta Lake concepts and Databricks SQL.</li><li>Exposure to PySpark for data transformation tasks.</li></ul></div><div> 
SQL: 
<ul><li>Solid SQL skills: joins, CTEs, window functions, aggregations, and basic performance awareness.</li><li>Experience writing SQL for data transformation and validation in a cloud data warehouse.</li></ul></div><div> 
Pipeline Engineering: 
<ul><li>Experience building or supporting ELT pipelines with monitoring and basic data validation.</li><li>Familiarity with pipeline orchestration tools such as Azure Data Factory or Databricks Workflows.</li></ul></div><div> 
Python: 
<ul><li>Basic to intermediate Python skills for data processing, scripting, and automation.</li><li>Familiarity with PySpark is a plus.</li></ul></div><div> 
Data Modeling: 
<ul><li>Understanding of star/snowflake schemas and fact &amp; dimension table concepts.</li><li>Exposure to Lakehouse or medallion architecture (Bronze/Silver/Gold) is a plus.</li></ul></div><div> 
Soft Skills 
<ul><li>Curious and eager to learn with a proactive approach to problem-solving.</li><li>Good communication skills &mdash; able to collaborate across technical and non-technical teams.</li><li>Attention to detail and a strong sense of data quality.</li><li>Comfortable working in a collaborative, fast-paced, and remote team environment.</li></ul></div><div> 
Preferred Additional Requirements 
<ul><li>Experience with Databricks or Azure Synapse Analytics.</li><li>Familiarity with D365 CRM or Similar data structures.</li><li>Exposure to Git-based workflows and CI/CD practices for data pipeline deployments.</li><li>Experience in a humanitarian, nonprofit, or international development context.</li></ul></div> 
Working Environment 
Remote 
PROFESSIONAL STANDARDS
All International Rescue Committee workers must adhere to the core values and principles outlined in IRC Way - Standards for Professional Conduct. Our Standards are Integrity, Service, Equality and Accountability. In accordance with these values, the IRC operates and enforces policies on Safeguarding, Conflicts of Interest, Fiscal Integrity, and Reporting Wrongdoing and Protection from Retaliation. IRC is committed to take all necessary preventive measures and create an environment where people feel safe, and to take all necessary actions and corrective measures when harm occurs. IRC builds teams of professionals who promote critical reflection, power sharing, debate, and objectivity to deliver the best possible services to our clients.
Cookies: https://careers.rescue.org/us/en/cookiesettings
#li-1</div>

Data Engineer

Cloud Enterprise Business Solutions (CEBS)

<div>
 
 
 Data Engineer
 
 
 
 We are looking for a Data Engineer with strong experience in Azure data services, Azure Databricks, PySpark, and Power BI to join our customer analytics and insights team. You will play a key role in bridging the gap between business requirements and technical delivery working across data engineering, analytics, and stakeholder communication.
 
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Work closely with business stakeholders to gather, understand, and translate business requirements into scalable data solutions.
 </li>
 <li>
 Design, build, and optimize data pipelines in Azure Databricks using PySpark and SQL.
 </li>
 <li>
 Collaborate with analysts and product owners to deliver ad-hoc analyses, as well as end-to-end production-grade data solutions.
 </li>
 <li>
 Manage and maintain data lakes, ensuring efficient data ingestion, transformation, and storage.
 </li>
 <li>
 Develop data models and datasets optimized for Power BI dashboards and self-service analytics as well as design and create dashboards.
 </li>
 <li>
 Participate in CI/CD and DevOps processes for automated deployment and monitoring of data workflows.
 </li>
 <li>
 Communicate technical concepts effectively to non-technical business users, providing clarity and actionable insights.
 </li>
 </ul>
 
 
 
 
 
 Key Qualifications
 
 
 <ul>
 <li>
 3+ years of experience as a Data Engineer. Experience in Azure data ecosystem (Azure Data Factory, Azure Data Lake Gen2, Azure Databricks) is a plus.
 </li>
 <li>
 Strong hands-on experience in PySpark, SQL, and Python for data transformation and pipeline automation.
 </li>
 <li>
 Experience designing and managing data pipelines and ETL processes using Databricks and Delta Lake.
 </li>
 <li>
 Experience in Data Visualization and a good understanding of Power BI data.
 </li>
 <li>
 Experience in stakeholder management. Translating business needs into data-driven solutions and presenting findings clearly.
 </li>
 <li>
 Familiarity with DevOps concepts, Git, and CI/CD pipelines in Azure DevOps.
 </li>
 <li>
 Solid understanding of data governance, data quality, and metadata management principles.
 </li>
 </ul>
 
 
 
 
 
 What&rsquo;s in it for you
 
 
 <ul>
 <li>
 Competitive salary
 </li>
 <li>
 Employees' Provident Fund, medical and other incentives
 </li>
 <li>
 Unique working environment where you communicate and work directly with international clients
 </li>
 <li>
 Self-development opportunities
 </li>
 </ul>
</div>

Confiz

<div>
 We are seeking a
 
 Principal Data Engineer
 
 with 5+ years of hands-on experience in the modern cloud data stack. This role is ideal for someone passionate about building robust, scalable data solutions and who thrives in agile, collaborative environments.
 
 
 The core technical stack centers around
 
 Databricks / PySpark
 
 for large-scale data processing,
 
 DBT
 
 for transformation,
 
 Astronomer / Airflow
 
 for orchestration (with
 
 Cosmos
 
 to run DBT DAGs natively in Airflow), and
 
 Snowflake
 
 as the cloud data warehouse.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Build and maintain scalable data pipelines using DBT and Astronomer/Airflow for batch and incremental data processing.
 </li>
 <li>
 Develop modular DBT transformation layers (staging &rarr; intermediate &rarr; mart) with robust testing, documentation, and incremental model strategies.
 </li>
 <li>
 Orchestrate end-to-end workflows on Astronomer / Airflow, using Cosmos to trigger and manage DBT models as native Airflow DAGs.
 </li>
 <li>
 Design and optimize Snowflake schemas, queries, and cost controls for analytical workloads.
 </li>
 <li>
 Enforce data quality standards through DBT tests and pipeline observability tooling.
 </li>
 <li>
 Write clean, well-tested Python and SQL code and actively participate in code reviews.
 </li>
 <li>
 Lead and mentor a team of data engineers; contribute to sprint planning, architectural decisions, and technical standards.
 
 
 </li>
 </ul>
 
 Required Skills &amp; Experience
 
 
 
 <ul>
 <li>
 Databricks &amp; PySpark: Delta Lake, batch and streaming workloads, cluster and cost optimization.
 </li>
 <li>
 DBT (Core &amp; Cloud): Advanced data modelling patterns, incremental strategies, custom tests, and CI/CD integration.
 </li>
 <li>
 Astronomer / Airflow: DAG authoring, Cosmos for DBT orchestration, and pipeline observability.
 </li>
 <li>
 Snowflake: Data modelling, query performance tuning, access control, and cost governance.
 </li>
 <li>
 Python and SQL: Strong programming skills with a focus on modular, maintainable, and testable code.
 </li>
 <li>
 Cloud platform: Hands-on experience with Azure or AWS.
 </li>
 <li>
 Agile &amp; CI/CD: Comfortable working in agile teams with a CI/CD development mindset.
 </li>
 <li>
 Degree: Bachelor&rsquo;s in Computer Science or a related discipline.
 
 
 </li>
 </ul>
 We have an amazing team of 700+ individuals working on highly innovative enterprise projects &amp; products. Our customer base includes Fortune 100 retail and CPG companies, leading store chains, fast-growth fintech, and multiple Silicon Valley startups.
 
 
 What makes Confiz stand out is our focus on processes and culture. Confiz is
 
 ISO 9001:2015
 
 (QMS),
 
 ISO 27001:2022
 
 (ISMS),
 
 ISO 20000-1:2018
 
 (ITSM),
 
 ISO 14001:2015
 
 (EMS),
 
 ISO 45001:2018
 
 (OHSMS) Certified. We have a vibrant culture of learning via collaboration and making workplace fun.
 
 
 People who work with us work with cutting-edge technologies while contributing success to the company as well as to themselves.
 
 
 To know more about Confiz Limited, visit: https://www.linkedin.com/company/confiz-pakistan/
</div>

Principal Data Engineer (Databricks / PySpark, DBT & Astronomer / Airflow)

<div>We are looking for a Data Engineer with 2&ndash;4 years of experience to design, build, and maintain data pipelines that enable efficient data processing and analytics. The ideal candidate will have expertise in SQL, data modeling, and modern data engineering tools and frameworks, and will work closely with data analysts, BI developers, and business teams to ensure reliable and high-quality data flows.
Responsibilities:
<ul><li>Design, develop, and maintain ETL/ELT data pipelines to support business analytics and reporting</li>
<li>Implement data models optimized for performance, scalability, and business needs</li>
<li>Develop and manage data integration workflows using modern ETL tools and orchestration frameworks</li>
<li>Ensure data quality, integrity, and consistency across various systems</li>
<li>Optimize SQL queries and database performance for efficient data retrieval</li>
<li>Collaborate with data scientists, analysts, and BI teams to provide well-structured data for insights</li>
<li>Monitor and troubleshoot data pipeline failures, ensuring minimal downtime</li>
<li>Implement best practices in data engineering, including documentation, version control, and automation</li>
</ul>
Requirements :
<ul><li>2&ndash;4 years of experience in data engineering, ETL/ELT, and data pipeline development (Oracle, Informatica, Azure)</li>
<li>Strong proficiency in SQL for data transformation, query optimization, and performance tuning</li>
<li>Hands-on experience with modern ETL/ELT tools and orchestration frameworks (e.g., ADF, Informatica, Apache Airflow, dbt, or similar)</li>
<li>Knowledge of data modeling principles (dimensional modeling, normalization, denormalization)</li>
<li>Familiarity with relational database systems such as Oracle, MS SQL Server, or similar</li>
<li>Experience with a programming language such as Python for data processing and automation</li>
<li>Strong problem-solving skills with the ability to troubleshoot and optimize data workflows</li>
<li>Ability to work independently and collaborate with cross-functional teams</li>
<li>Good understanding of data governance, security, and compliance best practices</li>
</ul>
Preferred Qualifications :
<ul><li>Bachelor&rsquo;s degree in Computer Science, Engineering, or related field (or equivalent experience)</li>
<li>Experience with cloud data platforms (AWS, Azure, or GCP)</li>
<li>Exposure to CI/CD for data pipelines and version control systems like Git</li>
<li>Familiarity with big data technologies (e.g., Apache Spark) or data warehousing solutions</li>
</ul>
We have a global team of 700 + amazing individuals working on highly innovative enterprise projects &amp; products. Our customer base includes Fortune 100 retail and CPG companies, leading store chains, fast growth fintech, and multiple Silicon Valley startups. 
 
What makes Confiz stand out is our focus on processes and culture. Confiz is ISO 9001:2015 (QMS), ISO 27001:2022 (ISMS), ISO 20000-1:2018 (ITSM) and ISO 14001:2015 (EMS) Certified. We have a vibrant culture of learning via collaboration and making workplace fun. 
 
People who work with us work with cutting-edge technologies while contributing success to the company as well as to themselves. 
To know more about Confiz, visit: https://www.linkedin.com/company/confiz/</div>

Senior Data Engineer

Nayatel

<div>
 
 
 Job Requirements:
 
 
 <ul>
 <li>
 Design, develop, and optimize scalable ETL/ELT pipelines and data workflows using Python and SQL.
 </li>
 <li>
 Build and maintain batch and real-time data processing systems using tools such as Apache Airflow, Apache Kafka, and DBT.
 </li>
 <li>
 Develop robust data integration solutions to ingest data from multiple sources into data warehouses.
 </li>
 <li>
 Collaborate with stakeholders and cross-functional teams to gather business requirements and translate them into scalable data models and technical solutions.
 </li>
 <li>
 Perform data modeling and schema design for analytical and operational reporting systems.
 </li>
 <li>
 Work with relational databases such as Oracle, PostgreSQL, and MySQL for querying, optimization, and data warehousing.
 </li>
 <li>
 Implement and maintain real-time streaming solutions using Apache Kafka and related technologies.
 </li>
 <li>
 Monitor data pipelines and ensure data quality, consistency, integrity, reliability, and performance across systems.
 </li>
 <li>
 Troubleshoot and resolve issues related to ETL processes, database performance, and data infrastructure.
 </li>
 <li>
 Optimize SQL queries, database operations, and pipeline performance for large-scale data processing.
 </li>
 <li>
 Document data architectures, workflows, technical processes, and system designs to maintain clear and up-to-date technical documentation.
 </li>
 <li>
 Work closely with software engineering, DevOps, and infrastructure teams to ensure seamless integration and scalability of data platforms.
 </li>
 </ul>
 
 
 
 
 
 Requirements:
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Information Technology, Software Engineering, or a related field.
 </li>
 <li>
 1 to 2 years of relevant experience
 </li>
 <li>
 Strong expertise in data engineering tools and technologies including Apache Airflow, Apache Kafka, DBT, and relational databases such as Oracle, PostgreSQL, and MySQL.
 </li>
 <li>
 Good understanding of data modeling, data warehousing, real-time and batch data processing, SQL optimization, troubleshooting, and data pipeline performance management.
 </li>
 <li>
 Familiarity with cloud platforms, modern data engineering practices, CI/CD, and workflow automation.
 </li>
 <li>
 Strong analytical, problem-solving, and communication skills with the ability to work in a collaborative environment.
 </li>
 </ul>
 
 
 
 
 
 Why Nayatel?
 
 
 
 We provide:
 
 <ul>
 <li>
 Challenging environment
 </li>
 <li>
 Open door policy
 </li>
 <li>
 Respect, dignity, and protection
 </li>
 <li>
 Training, mentoring, and coaching in soft and hard skills to transform you as a future leader
 </li>
 <li>
 Representation in external forums (University lecturers, advisory boards, etc.)
 </li>
 <li>
 Excellent rewards for out of the box thinker, doers, and implementers
 </li>
 <li>
 Equal opportunity, and merit.
 </li>
 </ul>
 
 
 
 
 
 Hiring Procedure:
 
 
 <ul>
 <li>
 CV Shortlisting
 </li>
 <li>
 Technical Test
 </li>
 <li>
 Initial Interview
 </li>
 <li>
 IQ/Personality Assessment Tests
 </li>
 <li>
 Final interview
 </li>
 <li>
 Medical Screening
 </li>
 <li>
 Joining
 </li>
 </ul>
</div>

Polarity Holdings

Starting Salary: Rs 501,000 PKR / monthSchedule: U.S. Eastern, Monday through FridayLocation: 100% Remote, Full-TimeAbout the RoleFalcon Scaling and PolarityIQ build private capital markets intelligence products. Our clients are family offices, institutional LPs, fund managers, investment banks, and registered investment advisors. They pay premium prices for verified, decision-maker-level intelligence on capital allocators worldwide.We operate a commercially active library of more than two hundred data products spanning family offices, institutional investors, venture capital, private equity, fund of funds, mutual funds, real estate, and high net worth individuals. Our flagship products include Family Office MAX (25,000+ executives across 10,000+ family offices) and LP MAX Bundle (80,000+ contacts across 17,000+ institutional LPs representing over $2 trillion in AUM).The Senior Data Engineer (Full Chain Builder) owns Project NOVA: the three-stage production pipeline that acquires records at scale, enriches them to the granularity capital allocators will pay for, and activates them inside PolarityIQ through agentic retrieval that surfaces signals autonomously.This is hands-on, high-autonomy work. You will build original scraping pipelines, architect multi-provider enrichment waterfalls, deploy production RAG systems, and build the agentic retrieval layer across our intelligence library. You ship products paying customers rely on, not internal demos.Before You ApplyIf your resume does not name a specific client, a real user volume, and what breaks when your system goes down: do not apply.If you have not deployed at least one production RAG system that a non-technical user relied on: do not apply.If Claude Code is not already part of your daily workflow, this role will move too fast for you.CompensationStarting salary is Rs 501,000 PKR per month. The role includes a revenue-sharing component tied directly to your contributions. You are paid weekly, on time.Strong performers regularly see total earnings scale meaningfully within the first four to eight weeks, with continued upside as contributions compound. On-target monthly earnings can exceed Rs 1,000,000 PKR within six to eight months.How You Enter &mdash; The 30-Day SprintThis role begins with a paid, deliverable-based 30-Day Build and Monetization Sprint at Rs 501,000 per month. You do not need to leave your current position. You operate on your own schedule, deploy existing products against real demand, and report what happens when your work meets the market.This is not a trial period. It is a real operating environment. At day 31, both sides hold 30 days of evidence. You will know whether the earnings trajectory and autonomy are real. We will know how you operate under real conditions.What You'll OwnAcquire &mdash; Sourcing and Scraping<ul><li>Build scraping pipelines against family office sites, regulatory filings, SEC EDGAR, state corporate registration databases, and professional networks.</li><li>Handle production anti-bot environments &mdash; Cloudflare, DataDome, PerimeterX &mdash; through residential proxies, CAPTCHA solvers, and stealth browser configurations.</li><li>Orchestrate recurring scraping with Apache Airflow, Prefect, or equivalent. Scheduled, monitored, recoverable.</li><li>Validate sourced records against schema contracts using Pydantic or equivalent. Every record passes the validation gate before entering the pipeline.</li></ul>Enrich &mdash; Multi-Provider Waterfalls<ul><li>Build and manage multi-source enrichment waterfalls using Clay.com, Apollo, Hunter, People Data Labs, Clearbit, and similar platforms.</li><li>Know the cost, coverage, and reliability tradeoffs between providers field by field. Build waterfalls that minimize cost while maximizing coverage.</li><li>Add granularity dimensions that matter: decision-maker layer, investment thesis, activity signals, relationship graph, structural classification, validation metadata.</li><li>Apply data hygiene principles across all pipelines: bounce rates, email verification, contact scoring, stale record detection.</li><li>Operate orchestration tooling that lets enrichment chains run end-to-end without manual stitching: n8n, Apache Airflow, Prefect, Make, or equivalent. The waterfall is one workflow, not a sequence of disconnected scripts.</li><li>Build cost-efficient pipelines that scale without proportional cost growth.</li></ul>Activate &mdash; Agentic RAG and RetrievalPolarityIQ's core intelligence layer is built on RAG. This is not experimental. It is the foundation of how our platform transforms raw family office data into queryable, actionable intelligence.<ul><li>Architect end-to-end RAG systems: document ingestion, chunking strategy, embedding model selection, vector database architecture, retrieval pipeline design.</li><li>Select and justify vector database choices (ChromaDB, Pinecone, Supabase pgvector, Weaviate, or equivalent) based on cost, latency, and scale requirements.</li><li>Implement hybrid retrieval strategies combining semantic vector search with keyword matching (BM25) for higher relevance and accuracy.</li><li>Build retrieval evaluation loops. Assess whether your system returns accurate, grounded results and diagnose when it does not.</li><li>Design and deploy autonomous AI agents using LangChain, CrewAI, or equivalent frameworks. Agents that gather, validate, and synthesize intelligence across data sources.</li><li>Integrate agentic workflows into the PolarityIQ platform so users receive signal delivery, not just search results.</li></ul>Database Architecture<ul><li>Own the architecture, integrity, and growth of PolarityIQ's core intelligence database.</li><li>Design and manage relational schema across Supabase/PostgreSQL, ensuring normalization, indexing, and query performance at scale.</li></ul>Technical StackScraping and AcquisitionScrapy, Playwright, curl_cffi, BeautifulSoup, Requests. Apify, Phantombuster, Browse AI at production scale. Anti-bot fluency: Cloudflare, DataDome, PerimeterX (named experience, not theoretical). Proxies: Bright Data, Oxylabs, Zyte, Smartproxy. CAPTCHA solvers: 2Captcha, Anti-Captcha, CapSolver. Orchestration: Apache Airflow, Prefect, AWS Lambda.EnrichmentClay.com as primary environment: tables, waterfalls, formulas, AI columns. Provider depth: Apollo, Hunter, People Data Labs, Clearbit, BetterContact, Cognism. Validation: Pydantic, Pandera, or Great Expectations applied to scraping output.RAG and Agentic SystemsProduction RAG deployment covering document ingestion, chunking, embeddings, hybrid retrieval, re-ranking, grounding. Vector databases: ChromaDB, Pinecone, Supabase pgvector, Weaviate. Agent frameworks: LangChain, CrewAI, LlamaIndex. LLM APIs: OpenAI, Anthropic Claude, Gemini, with understanding of cost, latency, and reliability tradeoffs.Claude Code &mdash; Non-NegotiableYou operate Claude Code in terminal-based, agentic workflows. Not as a code completer but as a development collaborator you direct, correct, and build with autonomously. You know its limits and call them without hand-holding.Development and InfrastructureBackend with Python, Node.js, or similar. SQL, relational schema design, query optimization. Managed platforms (Supabase, PostgreSQL). API integration (REST, GraphQL, webhooks). Git / GitHub.Who You AreThe technical skills matter. This section matters more.You take ownership before being asked. You measure yourself by outcomes, not activity. You are honest, even when it is uncomfortable. You are reliable, not occasionally but consistently. You are resourceful enough to treat every dollar spent like it is coming out of your own pocket.Your thought process is disciplined. You verify before you assert. You distinguish between facts, inferences, and conclusions, and you never conflate them. You test your assumptions before acting. You are willing to challenge your own hypotheses when the evidence points elsewhere.You use AI extensively but think independently first. Claude Code feels like a natural extension of how you work. You know when it is wrong, when it is shallow, and when to apply the human layer of judgment no prompt can replicate.You communicate in flawless English. Your first draft should be publishable. You do not require heavy editing cycles.Job Type: Full-timePay: Rs501,000.00 per monthEducation:<ul><li>Master's (Preferred)</li></ul>Language:<ul><li>English (Preferred)</li></ul>Work Location: In person

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