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data pipeline engineer

AlphaBOLD

<div><h2 class="jobSectionHeader">JOB SUMMARY</h2>

Alphabold is looking for a skilled Data Engineer with 3&ndash;5 years of experience to design, build, and maintain scalable data pipelines and infrastructure. The ideal candidate will have strong expertise in data processing, database systems, and cloud platforms, enabling efficient data flow and analytics across the organization.
<h3 class="jobSectionHeader">
Key Responsibilities</h3>
<ul><li>Design, develop, and maintain scalable ETL/ELT data pipelines</li>
<li>Build and optimize data architectures, data lakes, and data warehouses</li>
<li>Ensure data quality, integrity, and reliability across systems</li>
<li>Collaborate with data analysts, data scientists, and business stakeholders to deliver data solutions</li>
<li>Develop and manage batch and real-time data processing systems</li>
<li>Monitor and troubleshoot data pipeline performance and failures</li>
<li>Implement data governance, security, and compliance best practices</li>
<li>Automate workflows and improve data engineering processes</li>
</ul><h3 class="jobSectionHeader">Required Skills &amp; Qualifications</h3>
<ul><li>3&ndash;5 years of experience in data engineering or related roles</li>
<li>Strong proficiency in SQL and Python (or Scala/Java)</li>
<li>Hands-on experience with ETL tools and frameworks (e.g., Apache Airflow, Talend, Informatica)</li>
<li>Experience with big data technologies such as Apache Spark, Hadoop, or Kafka</li>
<li>Solid understanding of data warehousing concepts and modeling (Star/Snowflake schema)</li>
<li>Experience with cloud platforms like AWS, Azure, or Google Cloud</li>
<li>Familiarity with relational and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB)</li>
<li>Experience with version control systems (e.g., Git)</li>
</ul><h3 class="jobSectionHeader">Preferred Qualifications</h3>
<ul><li>Experience with containerization tools like Docker and orchestration tools like Kubernetes</li>
<li>Knowledge of CI/CD pipelines and DevOps practices</li>
<li>Familiarity with data visualization tools (e.g., Power BI, Tableau)</li>
<li>Understanding of streaming data systems and real-time analytics</li>
</ul><h3 class="jobSectionHeader">Soft Skills</h3>
<ul><li>Strong problem-solving and analytical skills</li>
<li>Good communication and collaboration abilities</li>
<li>Ability to work in a fast-paced, agile environment</li>
<li>Attention to detail and commitment to data accuracy</li>
</ul><h3 class="jobSectionHeader">Education</h3>
<ul><li>Bachelor&rsquo;s degree in Computer Science, Engineering, Information Technology, or a related field</li>
</ul><h3 class="jobSectionHeader">Nice to Have</h3>
<ul><li>Certifications in cloud platforms (AWS, Azure, GCP)</li>
<li>Experience working with large-scale distributed systems</li></ul></div>

Data Engineer

ibex

<div>
 We are seeking a highly motivated and responsible
 
 Data Engineer
 
 to join our dynamic team. This role requires hands-on experience in building scalable data pipelines, managing structured and unstructured databases, and supporting end-to-end data operations. The ideal candidate will bring strong problem-solving skills, a collaborative mindset, and a commitment to data excellence.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Design, develop, and manage reliable and scalable data pipelines.
 </li>
 <li>
 Clean, validate, and transform data from multiple sources for analytics and operational use.
 </li>
 <li>
 Work with large datasets and ensure high data quality and availability.
 </li>
 <li>
 Develop and maintain ETL workflows using standard tools and scripting.
 </li>
 <li>
 Automate data extraction, transformation, and loading processes across systems.
 </li>
 <li>
 Monitor and optimize performance of data workflows for speed and efficiency.
 </li>
 <li>
 Develop, maintain, and optimize complex SQL queries, stored procedures, functions, and views.
 </li>
 <li>
 Design and implement relational database schemas and indexing strategies.
 </li>
 <li>
 Ensure data integrity, security, and compliance within SQL Server environments.
 </li>
 <li>
 Work with MongoDB for storing and querying unstructured or semi-structured data.
 </li>
 <li>
 Design document-based data models and manage performance tuning for MongoDB.
 </li>
 <li>
 Handle replication and backup strategies where applicable.
 </li>
 <li>
 Analyze complex data requirements and translate them into efficient technical solutions.
 </li>
 <li>
 Identify data-related issues, perform root-cause analysis, and deliver timely resolutions.
 </li>
 <li>
 Work closely with data analysts, software engineers, and business stakeholders to understand requirements.
 </li>
 <li>
 Participate in code reviews, team planning sessions, and cross-functional meetings.
 </li>
 <li>
 Take ownership of assigned tasks with accountability and attention to detail.
 </li>
 <li>
 Exhibit a proactive approach to delivering solutions and supporting team goals.
 </li>
 <li>
 Contribute to architectural discussions and recommend improvements based on industry best practices.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Information Systems, or a related field.
 </li>
 <li>
 2&ndash;3 years of experience in data engineering or database development roles.
 </li>
 <li>
 Strong proficiency in SQL Server (T-SQL, indexing, optimization).
 </li>
 <li>
 Hands-on experience with MongoDB or other NoSQL technologies.
 </li>
 <li>
 Familiarity with data pipeline tools and ETL development.
 </li>
 <li>
 Working knowledge of Python or similar scripting languages.
 </li>
 <li>
 Understanding of data modeling, normalization, and data warehousing concepts.
 </li>
 <li>
 Strong analytical thinking and problem-solving skills.
 </li>
 <li>
 Excellent communication and teamwork abilities.
 </li>
 </ul>
</div>

Data Engineer, Tech

World Business Lenders, LLC

<div>About World Business Lenders (www.wbl.com) 
 
World Business Lenders (WBL) is proud to offer short-term, real estate-backed commercial loans to a diverse range of small and medium-sized businesses across the United States, especially those who may find it challenging to secure traditional financing.
Typically, the work schedule is from 9:00am to 6:00pm Eastern Time, Monday through Friday, though there might be times when additional hours are needed to meet business demands.
We&rsquo;re looking for someone with strong communication skills in both English, both spoken and written.<ul><li>
Please note that all resumes should be submitted in English.</li></ul> 
We are seeking two Data Analysts, one specializing in data engineering &amp; migration, and another focused on data pipeline &amp; automation. Candidates with strengths in either area are encouraged to apply.
Key Responsibilities:<ul><li>
Improved data pipelines (via automation) with quality checks to ensure data accuracy, consistency, and reliability throughout the entire data processing workflow, reducing manual intervention and minimizing errors.</li><li>
Migration of legacy systems to new systems, involving thorough analysis, seamless data transfer, and integration to enhance system performance and maintain continuity without disrupting existing operations.</li></ul> 

Requirements 
Required Education:
<ul><li>A Bachelor&rsquo;s degree in Computer Science, Engineering, Information Systems, or a related field is preferred &mdash; but we also highly value equivalent hands-on experience!</li></ul> 
Required Experience:<ul><li>
4 to 7 years of experience as a Data Engineer.</li><li>
We value practical, hands-on expertise that goes beyond just theoretical knowledge.</li></ul>
Required Background / Industry Experience:
Required for both roles:<ul><li>
Experience working with cloud-based data platforms and environments</li><li>
Strong SQL skills with data modeling experience for data warehouses</li><li>
Strong Python skills (especially notebooks) for building and maintaining data workflows</li><li>
Experience developing and maintaining ETL/ELT processes</li><li>
Experience working with data warehouses used by reporting/business teams</li><li>
Experience using Git/GitHub for version control in collaborative environments</li><li>
Understanding of data engineering best practices:</li><li>
Pipeline orchestration and dependency management</li><li>
Data quality, validation, and monitoring fundamentals</li></ul>
Required for migration-focused role:<ul><li>
Hands-on data migration experience:</li><li>
Schema mapping and transformation</li><li>
Data reconciliation and validation (must be strong here)</li><li>
Data quality checks, integrity validation, and issue resolution</li><li>
Backfills and historical data handling</li><li>
Cutover planning and execution</li></ul>
Required for automation-focused role:<ul><li>
Experience building and maintaining automated data pipelines:</li><li>
Scheduling, orchestration, and failure handling</li><li>
Workflow reliability, monitoring, and repeatability</li></ul>
Preferred:<ul><li>
Experience within Microsoft Fabric or broader Microsoft Azure data ecosystem</li><li>
Experience with orchestration tools such as Apache Airflow, Azure Data Factory, or Fabric pipelines</li><li>
Experience with data quality and observability practices:</li><li>
Validation frameworks, alerting, SLAs, monitoring</li><li>
Experience optimizing performance in data environments:</li><li>
Query tuning, partitioning, indexing, cost optimization</li><li>
Familiarity with modern data formats and large-scale processing:</li><li>
Parquet, Delta, incremental processing patterns</li><li>
Experience integrating with external systems:</li><li>
REST APIs, authentication, retries, error handling</li><li>
Exposure to CI/CD practices for data workflows:</li><li>
Git-based deployments, PR workflows, environment promotion</li></ul> 
Key Soft Skills:<ul><li>
Clear communication: can explain data issues, tradeoffs, and results to both technical and business stakeholders.</li><li>
Ownership &amp; accountability: takes end-to-end responsibility for pipelines, data quality, and outcomes.</li><li>
Problem-solving mindset: able to debug complex data issues and work through ambiguity independently.
</li><li>Collaboration: works effectively across engineering, analytics, and business teams.</li><li>
Adaptability: comfortable operating in evolving environments (migration, changing requirements, new tools).</li></ul> 
Technical Skills:<ul><li>
Proficiency in SQL, Python, cloud technologies, and data competency.</li></ul> 

Benefits 
<ul><li>
USD Base Salary.</li><li>
Enjoy Paid Time Off (PTO) after just 6 months of service.</li><li>
Full-time opportunity.</li><li>
Enjoy the freedom of a completely remote work environment!</li></ul></div>

Remote - Data Engineering Analyst

<div>
 
 About World Business Lenders (www.wbl.com)
 
 
 
 World Business Lenders (WBL) is proud to offer short-term, real estate-backed commercial loans to a diverse range of small and medium-sized businesses across the United States, especially those who may find it challenging to secure traditional financing.
 
 
 Typically, the work schedule is from 9:00am to 6:00pm Eastern Time, Monday through Friday, though there might be times when additional hours are needed to meet business demands.
 
 
 
 We're looking for someone with strong communication skills in both English, both spoken and written.
 
 
 
 <ul>
 <li>
 Please note that all resumes should be submitted in English.
 
 
 </li>
 </ul>
 
 We are seeking two Data Analysts, one specializing in data engineering &amp; migration, and another focused on data pipeline &amp; automation. Candidates with strengths in either area are encouraged to apply.
 
 
 
 
 Key Responsibilities:
 
 
 
 <ul>
 <li>
 Improved data pipelines (via automation) with quality checks to ensure data accuracy, consistency, and reliability throughout the entire data processing workflow, reducing manual intervention and minimizing errors
 </li>
 <li>
 Migration of legacy systems to new systems, involving thorough analysis, seamless data transfer, and integration to enhance system performance and maintain continuity without disrupting existing operations
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 
 Required Education:
 
 
 
 <ul>
 <li>
 A Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field is preferred &mdash; but we also highly value equivalent hands-on experience!
 
 
 </li>
 </ul>
 
 Required Experience:
 
 
 
 <ul>
 <li>
 4 to 7 years of experience as a Data Engineer
 </li>
 <li>
 We value practical, hands-on expertise that goes beyond just theoretical knowledge
 
 
 </li>
 </ul>
 
 Required Background / Industry Experience:
 
 
 
 
 Required for both roles:
 
 
 
 <ul>
 <li>
 Experience working with cloud-based data platforms and environments
 </li>
 <li>
 Strong SQL skills with data modeling experience for data warehouses
 </li>
 <li>
 Strong Python skills (especially notebooks) for building and maintaining data workflows
 </li>
 <li>
 Experience developing and maintaining ETL/ELT processes
 </li>
 <li>
 Experience working with data warehouses used by reporting/business teams
 </li>
 <li>
 Experience using Git/GitHub for version control in collaborative environments
 </li>
 <li>
 Understanding of data engineering best practices:
 </li>
 <li>
 Pipeline orchestration and dependency management
 </li>
 <li>
 Data quality, validation, and monitoring fundamentals
 
 
 </li>
 </ul>
 
 Required for migration-focused role:
 
 
 
 <ul>
 <li>
 Hands-on data migration experience:
 </li>
 <li>
 Schema mapping and transformation
 </li>
 <li>
 Data reconciliation and validation (must be strong here)
 </li>
 <li>
 Data quality checks, integrity validation, and issue resolution
 </li>
 <li>
 Backfills and historical data handling
 </li>
 <li>
 Cutover planning and execution
 
 
 </li>
 </ul>
 
 Required for automation-focused role:
 
 
 
 <ul>
 <li>
 Experience building and maintaining automated data pipelines:
 </li>
 <li>
 Scheduling, orchestration, and failure handling
 </li>
 <li>
 Workflow reliability, monitoring, and repeatability
 
 
 </li>
 </ul>
 
 Preferred:
 
 
 
 <ul>
 <li>
 Experience within Microsoft Fabric or broader Microsoft Azure data ecosystem
 </li>
 <li>
 Experience with orchestration tools such as Apache Airflow, Azure Data Factory, or Fabric pipelines
 </li>
 <li>
 Experience with data quality and observability practices:
 </li>
 <li>
 Validation frameworks, alerting, SLAs, monitoring
 </li>
 <li>
 Experience optimizing performance in data environments:
 </li>
 <li>
 Query tuning, partitioning, indexing, cost optimization
 </li>
 <li>
 Familiarity with modern data formats and large-scale processing:
 </li>
 <li>
 Parquet, Delta, incremental processing patterns
 </li>
 <li>
 Experience integrating with external systems:
 </li>
 <li>
 REST APIs, authentication, retries, error handling
 </li>
 <li>
 Exposure to CI/CD practices for data workflows:
 </li>
 <li>
 Git-based deployments, PR workflows, environment promotion
 
 
 </li>
 </ul>
 
 Key Soft Skills:
 
 
 
 <ul>
 <li>
 Clear communication: can explain data issues, tradeoffs, and results to both technical and business stakeholders
 </li>
 <li>
 Ownership &amp; accountability: takes end-to-end responsibility for pipelines, data quality, and outcomes
 </li>
 <li>
 Problem-solving mindset: able to debug complex data issues and work through ambiguity independently.
 </li>
 <li>
 Collaboration: works effectively across engineering, analytics, and business teams
 </li>
 <li>
 Adaptability: comfortable operating in evolving environments (migration, changing requirements, new tools)
 
 
 </li>
 </ul>
 
 Technical Skills:
 
 
 
 <ul>
 <li>
 Proficiency in SQL, Python, cloud technologies, and data competency
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 <ul>
 <li>
 USD Base Salary
 </li>
 <li>
 Enjoy Paid Time Off (PTO) after just 6 months of service
 </li>
 <li>
 Full-time opportunity
 </li>
 <li>
 Enjoy the freedom of a completely remote work environment!
 </li>
 </ul>
</div>

H2o Labs

Location: Onsite Shift: Night Shift Job Type: Full-TimeJob Overview:We are looking for a skilled and detail-oriented Data Engineer with 2&ndash;4 years of hands-on experience to join our growing team. The ideal candidate will be responsible for building, optimizing, and maintaining scalable data pipelines and architectures to support data-driven decision-making across the organization.Key Responsibilities:<ul><li>Design, develop, and maintain scalable ETL/ELT pipelines</li><li>Build and manage data warehouses and data lakes</li><li>Ensure data quality, integrity, and reliability across systems</li><li>Optimize and automate data workflows for performance and scalability</li><li>Collaborate with data analysts, scientists, and business stakeholders</li><li>Work with large datasets and ensure efficient data processing</li><li>Monitor and troubleshoot data-related issues</li><li>Implement data security and governance best practices</li><li>Communicate effectively with cross-functional teams and stakeholders</li></ul>Required Skills &amp; Qualifications:<ul><li>Bachelor&rsquo;s degree in Computer Science, IT, or related field</li><li>2&ndash;4 years of experience as a Data Engineer or similar role</li><li>Strong proficiency in SQL and database design</li><li>Hands-on experience with Python (or similar programming language)</li><li>Experience with ETL tools (e.g., Airflow, Talend, Informatica)</li><li>Familiarity with cloud platforms (AWS, GCP, or Azure)</li><li>Experience with big data tools (e.g., Hadoop, Spark)</li><li>Understanding of data warehousing concepts</li><li>Excellent communication and interpersonal skills</li><li>Strong problem-solving and analytical skills</li></ul>Preferred Qualifications:<ul><li>Experience with real-time data processing</li><li>Knowledge of Docker/Kubernetes</li><li>Familiarity with CI/CD pipelines</li><li>Experience working in agile environments</li></ul>Job Type: Full-timePay: Rs100,000.00 - Rs220,000.00 per monthWork Location: In person

Shahzada Group of Industries

We are seeking an experienced AI Infrastructure &amp; Automation Engineer to join our team. In this role, you will be the bridge between high-level AI application logic and the underlying hardware that powers it. You will own the responsibility of scaling our AI operations, ensuring our LLM workflows run efficiently on centralized GPU infrastructure, and automating our backend systems. If you have a passion for building robust AI pipelines and optimizing server performance, we want to hear from you.Key Responsibilities<ul><li>Infrastructure Management: Architect, deploy, and maintain centralized GPU server clusters to ensure high availability and performance for LLM training and inference.</li><li>LLM Integration: Develop and maintain backend logic to integrate Large Language Models (LLMs) into production-grade applications.</li><li>Automation: Build end-to-end automation workflows that reduce manual operational tasks, utilizing tools like N8N, Make, or custom Python scripts.</li><li>System Optimization: Monitor and tune server resources to maximize GPU utilization and minimize inference latency.</li><li>Pipeline Development: Create and manage data pipelines for ingestion, preprocessing, and model fine-tuning.</li><li>Scalability: Troubleshoot hardware/software bottlenecks and scale our infrastructure as our AI service demand grows.</li></ul>Required Qualifications<ul><li>Deep Technical Expertise: 3+ years of experience in AI/ML infrastructure, systems engineering, or a similar technical role.</li><li>GPU &amp; Server Knowledge: Hands-on experience with managing GPU-accelerated servers (e.g., NVIDIA stack, CUDA, and containerization with Docker/Kubernetes).</li><li>LLM Proficiency: Practical experience with deploying and fine-tuning LLMs (e.g., Llama, OpenAI API, Mistral) in production environments.</li><li>Programming: Strong proficiency in Python and experience with MLOps frameworks.</li><li>System Integration: Proven ability to connect APIs, webhooks, and databases to build cohesive, automated business workflows.</li><li>Problem-Solving: A &quot;builder&quot; mindset with the ability to identify infrastructure bottlenecks and implement solutions proactively.</li></ul>Job Type: Full-timePay: Rs80,000.00 - Rs120,000.00 per monthWork Location: In person

Lead AI Automation Engineer (LLM & GPU Infrastructure)

Motive

<div><div>Who we are:

Motive empowers the people who run physical operations with tools to make their work safer, more productive, and more profitable. For the first time ever, safety, operations and finance teams can manage their drivers, vehicles, equipment, and fleet related spend in a single system. Combined with industry leading AI, the Motive platform gives you complete visibility and control, and significantly reduces manual workloads by automating and simplifying tasks.

Motive serves nearly 100,000 customers &ndash; from Fortune 500 enterprises to small businesses &ndash; across a wide range of industries, including transportation and logistics, construction, energy, field service, manufacturing, agriculture, food and beverage, retail, and the public sector.

Visit gomotive.com to learn more.</div><div>

About the Role:

The Sales Data Quality Analyst II (L4) is a pivotal member of the GTM Strategy and Sales Operations organization, dedicated to ensuring that Salesforce data remains accurate, comprehensive, and actionable across all sales motions. Serving as the primary subject-matter expert for sales data integrity, this role focuses on account and contact data, segmentation, and global hierarchy management (including the UK and Mexico). The Analyst II will design and maintain sophisticated data quality frameworks, conduct deep-dive analyses using SQL and Salesforce, and convert complex data challenges into clear business insights and remediation strategies that bolster pipeline health, territory planning, and executive decision-making.

Responsibilities:
<ul>
<li>As a Sales Data Quality Analyst II, the person in this role is expected to:</li>
<li>Lead high-impact data quality investigations and diagnostics</li>
<li>Proactively identify data issues and anomalies across accounts, contacts, and opportunities.Use SQL and Salesforce reporting to perform root-cause analysis and quantify business impact.</li>
<li>Establish and maintain rigorous data quality standards</li>
<li>Help define what &quot;good&quot; looks like for sales data (e.g., completeness, consistency, and accuracy thresholds).Contribute to and maintain data quality scorecards, rules, and documentation.</li>
<li>Engineer and oversee proactive data monitoring frameworks</li>
<li>Build, maintain, and iterate on automated checks and recurring reports that monitor data health (e.g., duplicate detection, missing key fields, invalid hierarchies).Surface prioritized issue lists and trends to GTM stakeholders.Support segmentation and enrichment initiativesPartner with regional teams (e.g., UK contact enrichment, Mexico account segmentation) to define data requirements and coverage goals.Validate enrichment inputs and outputs, ensuring they meet agreed standards before they are rolled out to sales teams.</li>
<li>Architect account hierarchy and structural integrity</li>
<li>Support the design and maintenance of parent&ndash;child account hierarchies in Salesforce.Ensure that account structures reflect real-world corporate relationships and support roll-up reporting and planning.Partner with Sales, RevOps, and GTM StrategyWork closely with business stakeholders to understand how data is used in daily workflows and executive reporting.Translate data quality findings into clear, actionable recommendations tied to sales outcomes.</li>
<li>Standardize documentation and operationalize for scale</li>
<li>Create and maintain process documentation, runbooks, and data dictionaries related to key sales data objects and fields.Recommend process and system changes that reduce recurring data issues and support sustainable data quality improvements.</li>
</ul>
Qualifications:
<ul>
<li>Bachelor's degree in a quantitative field (e.g., Computer Science, Engineering, Statistics, Economics, Business Analytics) or equivalent practical experience in sales data, analytics, or operations.</li>
<li>Advanced SQL Proficiency: Expert ability to perform data validation, profiling, and reporting across large, complex datasets.</li>
<li>Salesforce Expertise: Strong working knowledge of Salesforce objects (Accounts, Contacts, Opportunities, custom GTM fields), including complex hierarchies and segmentation logic.</li>
<li>AI &amp; Automation Proficiency: Experience leveraging AI/ML and LLM-powered tools to accelerate analysis, documentation, and data quality investigations while applying strong human judgment and validation.</li>
<li>Data Enrichment: Familiarity with data enrichment workflows and rigorous quality checks for third-party data sources.</li>
<li>Analytical Problem-Solving: Ability to perform structured root-cause analysis and bridge technical issues with tangible business impact.</li>
<li>Strategic Prioritization: Proven comfort in prioritizing issues based on impact, effort, and evolving stakeholder needs.</li>
<li>Executive Communication: Ability to communicate complex findings in a clear, concise, and business-friendly way to sales leadership.</li>
<li>Stakeholder Management: Skill in managing expectations, aligning on priorities, and driving accountability for remediation plans.</li></ul></div> 

<div>Creating a diverse and inclusive workplace is one of Motive's core values. We are an equal opportunity employer and welcome people of different backgrounds, experiences, abilities and perspectives.

Please review our Candidate Privacy Notice here.

UK Candidate Privacy Notice here.

The applicant must be authorized to receive and access those commodities and technologies controlled under U.S. Export Administration Regulations. It is Motive's policy to require that employees be authorized to receive access to Motive products and technology.</div></div>

Sales Data Quality Analyst II

Explore 571+ Data pipeline engineer in Lahore this April. Find roles across top companies and apply now to boost your career.

571 data pipeline engineer jobs In Lahore

Data Engineer

Data Engineer, Tech

Remote - Data Engineering Analyst

Remote - Data Engineering Analyst

Data Engineer

Lead AI Automation Engineer (LLM & GPU Infrastructure)

Sales Data Quality Analyst II