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NorthBay Solutions

<div>
 &nbsp;
 
 
 
 
 
 
 
 Job Title:
 
 
 
 
 
 
 
 
 
 
 
 
 Data Engineer (Snowflake)
 
 
 
 
 
 
 
 
 
 
 
 
 
 Location:
 
 
 
 
 
 
 
 
 
 
 
 
 Hybrid - Lahore, Karachi, Islamabad
 
 
 
 
 
 
 
 
 
 
 
 
 
 Experience:
 
 
 
 
 
 
 
 
 
 
 
 
 6-8 years (Minimum 4-6 years of Snowflake experience)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Job Category:
 
 
 
 
 
 
 
 
 
 
 
 
 Data Engineering
 
 
 
 
 
 
 
 
 
 
 
 
 
 Key Responsibilities:
 
 
 
 
 
 
 <ul>
 <li>
 
 
 
 
 
 
 Database Design &amp; Development:
 
 
 
 
 
 
 <ul>
 <li>
 
 
 
 
 
 
 Utilize Snowflake to design, develop, and optimize data architecture.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Work with PostgreSQL and other databases to manage and manipulate data.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Lead conversion projects from SQL-based platforms to Snowflake.
 
 
 
 
 
 
 </li>
 </ul>
 </li>
 <li>
 
 
 
 
 
 
 Programming &amp; Scripting:
 
 
 
 
 
 
 <ul>
 <li>
 
 
 
 
 
 
 Develop robust applications and scripts using C#, Java, and Python, or other relevant technologies.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Write efficient Snowflake functions and stored procedures using JavaScript.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Implement big data solutions using Spark and PySpark (Plus).
 
 
 
 
 
 
 </li>
 </ul>
 </li>
 <li>
 
 
 
 
 
 
 Cloud Integration:
 
 
 
 
 
 
 <ul>
 <li>
 
 
 
 
 
 
 Implement data storage solutions using Amazon S3 (AWS).
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Integrate and manage data pipelines using AWS Glue (Plus).
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Utilize AWS Lambda for serverless computing (Plus).
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Contribute to cloud data strategies involving GCP (Plus).
 
 
 
 
 
 
 </li>
 </ul>
 </li>
 <li>
 
 
 
 
 
 
 Additional Database Management:
 
 
 
 
 
 
 <ul>
 <li>
 
 
 
 
 
 
 Work with Aurora and MSSQL for various data management tasks (Plus).
 
 
 
 
 
 
 </li>
 </ul>
 </li>
 </ul>
 
 
 
 
 
 
 Required Skills:
 
 
 
 
 
 
 <ul>
 <li>
 
 
 
 
 
 
 Languages:
 
 
 
 
 
 
 
 
 
 
 
 
 C#, Java, Python, or other relevant technologies
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Database:
 
 
 
 
 
 
 
 
 
 
 
 
 Snowflake (Design, Develop), PostgreSQL
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Cloud Tools:
 
 
 
 
 
 
 
 
 
 
 
 
 Amazon S3 (AWS)
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Scripting:
 
 
 
 
 
 
 
 
 
 
 
 
 JavaScript (for Snowflake functions and stored procedures)
 
 
 
 
 
 
 </li>
 </ul>
 
 
 
 
 
 
 Preferred Skills:
 
 
 
 
 
 
 <ul>
 <li>
 
 
 
 
 
 
 Big Data Technologies:
 
 
 
 
 
 
 
 
 
 
 
 
 Spark, PySpark
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Cloud Tools:
 
 
 
 
 
 
 
 
 
 
 
 
 AWS Glue, AWS Lambda, GCP
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Database:
 
 
 
 
 
 
 
 
 
 
 
 
 Aurora, MSSQL
 
 
 
 
 
 
 </li>
 </ul>
 
 
 
 
 
 
 Conversion:
 
 
 
 
 
 
 
 
 
 
 
 
 SQL to Snowflake code conversion
 
 
 
 
 
 
</div>

Data Engineer(Snow Flake)

Techbridge Consultancy Services

We are looking for a motivated Data Engineer with 3+ years of experience to join our growing data team. You will be responsible for building, optimizing, and maintaining data pipelines and solutions that support business intelligence, analytics, and automation. This is an onsite role in our Lahore office.Key Responsibilities<ul><li>Develop, maintain, and optimize ETL/ELT pipelines using Python and related libraries (Pandas, NumPy, PySpark).</li><li>Write and optimize complex SQL queries for PostgreSQL, SQL Server, and other RDBMS.</li><li>Work with AWS Cloud services (S3, Lambda, Glue, Athena, Step Functions, EventBridge) to design and manage scalable data workflows.</li><li>Handle data ingestion, transformation, and validation for reporting and analytics.</li><li>Automate manual processes and integrate data flows across different systems.</li><li>Collaborate with analysts and business teams to ensure reliable and timely delivery of datasets and reports.</li><li>Use Excel and other BI tools for quick data analysis and validation.</li><li>Ensure data quality, security, and compliance in all data operations.</li></ul>Required Skills<ul><li>3+ years of professional experience in data engineering, ETL, or backend development.</li><li>Strong proficiency in Python (Pandas, NumPy, PySpark).</li><li>Solid knowledge of SQL (PostgreSQL, SQL Server, or similar).</li><li>Experience with AWS Cloud services (S3, Lambda, Glue, Athena, Step Functions, EventBridge).</li><li>Hands-on experience in Excel for data validation and reporting.</li><li>Familiarity with data warehousing concepts and big data tools.</li><li>Understanding of data modeling, schema design, and performance optimization.</li><li>Strong problem-solving, analytical, and communication skills.</li></ul>Preferred<ul><li>Experience with job orchestration tools (Airflow, Step Functions, etc.).</li><li>Exposure to BI/Reporting tools (e.g., Power BI, QuickSight, Tableau).</li><li>Knowledge of APIs, REST, and data integration techniques.</li><li>Experience with Git and version control.</li></ul>What We Offer<ul><li>Opportunity to work with modern data engineering tools and AWS Cloud.</li><li>Professional growth in a collaborative and supportive environment.</li><li>Onsite role at a prime location in Gulberg III, Lahore</li></ul>Job Type: Full-timeApplication Question(s):<ul><li>How many years of professional experience do you have working with Python for data engineering or ETL pipelines?</li><li>How would you rate your proficiency in writing and optimizing SQL queries?</li><li>Are you comfortable working full-time onsite from 2:00 PM to 11:00 PM (PKT) in Gulberg III, Lahore?</li></ul>Work Location: In person

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

We are seeking a skilled Senior Data Engineer to support the modernization of existing Talend-based ETL pipelines into a modern data engineering ecosystem leveraging Python, dbt, Kafka, Apache NiFi, and orchestration tools such as Airflow or Dagster.You will work closely with senior engineers to migrate, build, test, and maintain high-quality data pipelines across the organization. This role is ideal for professionals with strong hands-on data engineering skills, a collaborative mindset, and an eagerness to work with modern data stack technologies.Key Responsibilities:Pipeline Migration &amp; Development● Assist in re-engineering legacy Talend pipelines into Python, dbt, and Airflow/Dagster workflows.● Ensure pipeline logic, data mappings, and tests are accurately replicated and validated.● Support both legacy and new pipeline environments during the transition period.Data Ingestion &amp; Processing● Develop and maintain data ingestion flows using Kafka, Apache NiFi, and REST APIs.● Work with batch and streaming data across structured, semi-structured, and unstructuredformats.● Implement data validation, quality checks, schema enforcement, and row-level transformations.Transformation &amp; Modeling● Contribute to dbt development (models, tests, documentation, snapshots).● Support transformation logic to maintain accuracy, maintainability, and lineage.Monitoring &amp; Maintenance● Monitor daily ETL/ELT workflows for failures, bottlenecks, or data quality issues.● Perform root-cause analysis and escalate complex issues when needed.● Optimize performance across data ingestion, processing, and transformation layers.Documentation &amp; Collaboration● Maintain well-structured documentation for pipeline logic, migration work, and data flows.● Collaborate with senior engineers, QA, data analysts, architects, and platform teams.● Participate in Agile ceremonies: stand-ups, planning, reviews, and retrospectives.Required Experience &amp; Qualification:● 5+ years of experience in Data Engineering or ETL development.● Demonstrated ability to design, build, and maintain robust ELT/ETL pipelines.● Proficiency writing production-grade code (preferably in Python).● Hands-on with SQL (including analytical queries, CTEs, window functions, optimization).● Experience building pipelines using orchestration tools (Airflow, Databricks Workflows, etc.).● Proven comfort with version control, automated testing, code review, CI/CD for data.● ++ Practical experience with Databricks: can confidently use Spark APIs, Delta Lake features(ACID, schema evolution, time travel), and Unity Catalog for data management &amp;amp; accessgovernance.● Familiarity with data quality frameworks welcomed.● Skilled in designing scalable, maintainable, and performant data models (e.g., star/snowflake,normalization, partitioning, incremental strategies).● Can articulate and justify trade-offs in storage, compute, and access layer designs.● Proactive in identifying and fixing pipeline/data quality issues.● Strong troubleshooting, debugging, and root cause analysis skills; goes beyond surface-levelsolutions.● Able to reason about idempotency, error handling, recovery, backfilling, and other criticalproduction concerns.● Actively seeks to understand how and why things work- Consistently dives deeper- Explains in depth, not just what was done but why, and what trade-offs were considered or- Excellent communicator: explains choices and solutions clearly, tailors depth for technical and non-technical audiences.Job Type: Full-timeApplication Question(s):<ul><li>How many years of experience do you have in data engineering or ETL development?</li><li>How would you rate your proficiency in writing and optimizing SQL queries?</li><li>This is an onsite position at our office in Gulberg, Lahore. Are you comfortable working onsite at this location? (Yes/No)</li></ul>Work Location: In person

Senior Data Engineer

Aqovia

<div>
 
 Why Aqovia?
 
 
 
 At the Intersection of Innovation and Impact, introducing Aqovia. Aqovia is an international technology firm dedicated to creating tangible value through the power of AI, data-driven, and bespoke software solutions and services.
 
 
 Our unique approach extends beyond traditional service and solutions delivery, we strategically invest in and nurture a diverse portfolio of promising companies operating across vital sectors including; financial services, health, infrastructure management, sustainability, education, and business intelligence.
 
 
 This commitment to innovation across a broad spectrum allows Aqovia to stay at the cutting edge, delivering transformative solutions and creating significant impact. For our clients and strategic partners, Aqovia offers a unique opportunity to be part of a dynamic and forward-thinking group shaping the future.
 
 
 
 Role Overview
 
 
 
 Aqovia is seeking a highly capable Principal Data Engineer to join our consulting projects team. This is a senior, client-facing role combining hands-on technical delivery with leadership, mentoring, and stakeholder engagement responsibilities.
 
 
 You will act as Chapter Lead for Data Engineering, setting technical standards, guiding best practices, and supporting the growth of data engineering capability across the organisation. You will also play a key role in shaping modern, scalable data solutions that support our clients&rsquo; sustainability and transformation goals.
 
 
 This role requires a strong blend of technical expertise, consultancy experience, leadership capability, and a proactive mindset.
 
 
 
 Key Responsibilities
 
 
 
 
 Leadership &amp; Chapter Ownership
 
 
 
 <ul>
 <li>
 Act as Chapter Lead for Data Engineering, providing technical leadership, mentoring, and guidance across the data engineering community.
 </li>
 <li>
 Set and uphold engineering standards, best practices, and ways of working.
 </li>
 <li>
 Take ownership and accountability for the quality, maintainability, and scalability of data engineering solutions.
 
 
 </li>
 </ul>
 
 Delivery &amp; Technical Responsibilities
 
 
 
 <ul>
 <li>
 Design, develop, modernise, and test data engineering pipelines, including ETL/ELT processes, reports, and data visualisations.
 </li>
 <li>
 Build and maintain robust real-time and batch data pipelines to meet evolving client and business needs.
 </li>
 <li>
 Load and transform customer data into target platforms using scalable and reusable patterns.
 </li>
 <li>
 Implement data management and integration solutions using APIs.
 </li>
 <li>
 Write complex, performant T-SQL queries and high-quality Python code.
 </li>
 <li>
 Ensure solutions are well-documented, reusable, maintainable, and production-ready.
 </li>
 <li>
 Apply source control best practices using Git and contribute to CI/CD pipelines.
 
 
 </li>
 </ul>
 
 Stakeholder &amp; Client Engagement
 
 
 
 <ul>
 <li>
 Elicit, analyse, and refine multi-stakeholder requirements, translating business needs into technical solutions.
 </li>
 <li>
 Act as a client-facing consultant, confidently engaging with technical and non-technical stakeholders.
 </li>
 <li>
 Collaborate closely with internal teams and client stakeholders to provide technical leadership and delivery assurance.
 </li>
 <li>
 Support pre-sales and sales activities where required, including solution shaping and technical input.
 
 
 </li>
 </ul>
 
 Key Technical Skills Required
 
 
 
 <ul>
 <li>
 Strong experience designing, building, testing, and deploying data pipelines on the Azure platform.
 </li>
 <li>
 Advanced T-SQL and Python development skills.
 </li>
 <li>
 Proven experience with Git and working within source-controlled, CI/CD-driven environments.
 </li>
 <li>
 Expertise in Data analytics platforms (such as Hadoop, Data Bricks or Azure Synapse), Columnar data formats (e.g., Parquet, ORC, Arrow, etc), on-prem to cloud migrations, and both SQL and NoSQL data stores.
 </li>
 <li>
 Strong knowledge of batch and real-time data pipeline architectures, including event streaming
 </li>
 <li>
 Experience in data deduplication, transformation, and conformance from source to target structures.
 </li>
 <li>
 Solid understanding of logical and physical data modelling and storage design.
 </li>
 <li>
 Ability to address observability, data governance, privacy, and architectural concerns.
 </li>
 <li>
 Comfortable working autonomously while adopting new tools and technologies quickly.
 
 
 </li>
 </ul>
 
 Soft Skills &amp; Core Competencies
 
 
 
 <ul>
 <li>
 Excellent communication skills (written and verbal), with the ability to engage confidently at all levels.
 </li>
 <li>
 Strong teamwork and collaboration mindset. Clear accountability and ownership for outcomes and delivery.
 </li>
 <li>
 Demonstrated leadership and mentoring capability.
 </li>
 <li>
 Effective time management and organisational skills.
 </li>
 <li>
 High adaptability and flexibility in fast-changing environments.
 </li>
 <li>
 Strong problem-solving and critical-thinking ability.
 </li>
 <li>
 Proactive, self-starting approach with clear initiative.
 
 
 </li>
 </ul>
 
 Nice to Have
 
 
 
 Experience preparing and curating data for data science workflows, including dataset construction, and ensuring data quality and lineage for model training and evaluation
 
 
 <ul>
 <li>
 Familiarity with Retrieval-Augmented Generation (RAG) architectures and their application in enterprise or client-facing data solutions.
 </li>
 <li>
 Knowledge of Infrastructure as code (IaC)
 </li>
 <li>
 Experience or exposure to Machine Learning concepts, pipelines, or production use cases.
 </li>
 <li>
 Broader software engineering or cloud-native development experience.
 
 
 </li>
 </ul>
 
 Joining Aqovia means:
 
 
 
 <ul>
 <li>
 Making a real difference: You'll be part of a team developing solutions that empower businesses while contributing to sustainable practices.
 </li>
 <li>
 Growth opportunities: We invest in our employees' development and offer a path for career advancement.
 </li>
 <li>
 Collaborative culture: We value teamwork, open communication, and a supportive environment.
 </li>
 <li>
 Competitive benefits package: TBC
 
 
 </li>
 </ul>
 If you're a problem-solver who thrives in a fast-paced environment and shares our commitment to positive impact, we encourage you to apply!
 
 
 
 Equal Opportunity Employer:
 
 
 
 At Aqovia, we believe in the strength of diversity. We strive to reflect the varied markets we serve and foster an inclusive culture where everyone feels welcome, valued, and empowered to be their authentic selves. As an equal opportunity employer, we are committed to embracing all forms of diversity across our organisation
</div>

Principal Data Engineer

CodeNinja

<div>About CodeNinja
CodeNinja is a full-stack AI delivery company that helps enterprises, governments, and software acquirers build and operate intelligence-driven systems for mission-critical workflows. We specialize in deploying AI into real operations&mdash;combining strong engineering fundamentals with AI-native delivery to create measurable value, resilience, and long-term ownership for our clients. Our global footprint and delivery model are supported by AI Labs, AI Pods, and Global Capability Centers, enabling teams to co-engineer scalable platforms across regions and time zones.
Role Purpose
Lead the ERP program&rsquo;s data strategy by ensuring data readiness, conceptual data modelling, reporting data sourcing, and structured data migration planning, enabling a reliable, unified data foundation across all modules.
Key Responsibilities<ul><li>Conduct comprehensive assessment of legacy data sources:</li></ul>
o Inventory, Maintenance (MRO), Procurement, HR, Technical Docs<ul><li>Identify:</li></ul>
o Data quality issues (duplicates, missing, inconsistencies)
o Data ownership and governance gaps
o Redundant/siloed datasets<ul><li>Define data cleansing and standardization approach</li><li>Produce Data Readiness Assessment Report</li><li>Define end-to-end Data Migration Strategy, including:</li></ul>
o Migration approach (phased, module-wise, or big-bang)
o Data prioritization (master data vs transactional vs historical)<ul><li>Develop Data Mapping Specifications:</li></ul>
o Legacy ERP field-level mappings
o Transformation rules and standardization logic
o Handling of missing/invalid data<ul><li>Define Data Cleansing &amp; Preparation Plan:</li></ul>
o Deduplication rules
o Data enrichment where required
o Validation checkpoints before migration<ul><li>Design Migration Execution Plan:</li></ul>
o Migration cycles (mock runs, dry runs, final cutover)
o Rollback strategy in case of failure
o Downtime and cutover planning<ul><li>Define Data Validation &amp; Reconciliation Framework:</li></ul>
o Pre-migration vs post-migration validation rules
o Reconciliation reports (counts, totals, relationships)
o Sign-off criteria for each module<ul><li>Produce key deliverables:</li></ul>
o Data Migration Plan
o Data Mapping Documents
o Data Validation &amp; Reconciliation Reports<ul><li>Identify and enable AI/ML use cases, such as:</li></ul>
o Predictive maintenance modeling
o Inventory demand forecasting
o Supplier performance analytics<ul><li>Leverage AI tools for:</li></ul>
o Data profiling and anomaly detection
o Data quality assessment and cleansing recommendations
o Advanced analytics and insights generation<ul><li>Define enterprise conceptual data model:</li></ul>
o Assets, Inventory, Work Orders, Suppliers, Workforce, Technical Docs<ul><li>Establish:</li></ul>
o Entity relationships
o Master data definitions
o Data standardization rules<ul><li>Support BI teams for dashboards and analytics</li><li>Align data models with business workflows</li><li>Ensure requirements are data-feasible and consistent</li></ul> 
Requirements 
3. Required Skills &amp; Experience
Mandatory<ul><li> 5 - 8 years in Data Analyst / Data Architecture roles</li><li>Experience in large-scale ERP or enterprise data transformation programs</li><li>Strong expertise in:</li></ul>
o Data modelling (conceptual &amp; logical)
o Data migration and cleansing
o Data warehousing and reporting
Technical Expertise<ul><li>Strong knowledge of:</li></ul>
o ETL processes and migration tools
o SQL and relational databases
o API-based integrations<ul><li>Experience with BI tools (Power BI, Tableau)</li></ul>
Preferred<ul><li>Experience in ERP &amp; Enterprise Data Management (logistics, manufacturing)</li><li>Exposure to:</li></ul>
o Maintenance (MRO) data
o Inventory systems
o Technical documentation repositories<ul><li>Demonstrated experience using AI/ML tools or platforms, such as:</li></ul>
o Data analysis and prediction tools
o AI-assisted data modeling or profiling tools<ul><li>Ability to translate data into AI-driven insights for decision-making</li></ul>
Why Join CodeNinja?<ul><li>
Work on impactful ERP transformation projects at enterprise scale
</li><li>Shape end-to-end data strategy, migration, and architecture
</li><li>Leverage AI/ML for advanced data insights and analytics
</li><li>Collaborate with cross-functional teams and drive business decisions
</li><li>Build scalable data models and governance frameworks
</li><li>Grow in a culture of innovation, ownership, and continuous learning</li></ul>
Equal Opportunity Statement
We are an equal opportunity employer and are committed to fostering an inclusive, diverse, and equitable workplace. We do not discriminate based on race, religion, gender, age, disability, nationality, marital status, or any other protected characteristic under applicable law. We encourage candidates from all backgrounds to apply. 
Benefits 
<ul><li>
Provident Fund</li><li>
Gym Membership
</li><li>Leaves as per the company policy
</li><li>Company-paid trips
</li><li>Easy Loan Facility for Employees
</li><li>Yearly increment
</li><li>Maternity Benefits (Leaves &amp; WFH)
</li><li>Health Insurance (Maternity covered) &ndash; includes spouse and parents (till age 80)</li></ul></div>

Data Analyst/Data Architect

CodeNinja Inc.

<div>
 
 About CodeNinja
 
 
 
 
 CodeNinja
 
 is a full-stack AI delivery company that helps enterprises, governments, and software acquirers build and operate intelligence-driven systems for mission-critical workflows. We specialize in deploying AI into real operations&mdash;combining strong engineering fundamentals with AI-native delivery to create measurable value, resilience, and long-term ownership for our clients. Our global footprint and delivery model are supported by AI Labs, AI Pods, and Global Capability Centers, enabling teams to co-engineer scalable platforms across regions and time zones.
 
 
 
 
 Role Purpose
 
 
 
 
 Lead the ERP program's data strategy by ensuring data readiness, conceptual data modelling, reporting data sourcing, and structured data migration planning, enabling a reliable, unified data foundation across all modules.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Conduct comprehensive assessment of legacy data sources:
 </li>
 <li>
 Inventory, Maintenance (MRO), Procurement, HR, Technical Docs
 </li>
 <li>
 Identify:
 </li>
 <li>
 Data quality issues (duplicates, missing, inconsistencies)
 </li>
 <li>
 Data ownership and governance gaps
 </li>
 <li>
 Redundant/siloed datasets
 </li>
 <li>
 Define data cleansing and standardization approach
 </li>
 <li>
 Produce Data Readiness Assessment Report
 </li>
 <li>
 Define end-to-end Data Migration Strategy, including:
 </li>
 <li>
 Migration approach (phased, module-wise, or big-bang)
 </li>
 <li>
 Data prioritization (master data vs transactional vs historical)
 </li>
 <li>
 Develop Data Mapping Specifications:
 </li>
 <li>
 Legacy &rarr; ERP field-level mappings
 </li>
 <li>
 Transformation rules and standardization logic
 </li>
 <li>
 Handling of missing/invalid data
 </li>
 <li>
 Define Data Cleansing &amp; Preparation Plan:
 </li>
 <li>
 Deduplication rules
 </li>
 <li>
 Data enrichment where required
 </li>
 <li>
 Validation checkpoints before migration
 </li>
 <li>
 Design Migration Execution Plan:
 </li>
 <li>
 Migration cycles (mock runs, dry runs, final cutover)
 </li>
 <li>
 Rollback strategy in case of failure
 </li>
 <li>
 Downtime and cutover planning
 </li>
 <li>
 Define Data Validation &amp; Reconciliation Framework:
 </li>
 <li>
 Pre-migration vs post-migration validation rules
 </li>
 <li>
 Reconciliation reports (counts, totals, relationships)
 </li>
 <li>
 Sign-off criteria for each module
 </li>
 <li>
 Produce key deliverables:
 </li>
 <li>
 Data Migration Plan
 </li>
 <li>
 Data Mapping Documents
 </li>
 <li>
 Data Validation &amp; Reconciliation Reports
 </li>
 <li>
 Identify and enable AI/ML use cases, such as:
 </li>
 <li>
 Predictive maintenance modeling
 </li>
 <li>
 Inventory demand forecasting
 </li>
 <li>
 Supplier performance analytics
 </li>
 <li>
 Leverage AI tools for:
 </li>
 <li>
 Data profiling and anomaly detection
 </li>
 <li>
 Data quality assessment and cleansing recommendations
 </li>
 <li>
 Advanced analytics and insights generation
 </li>
 <li>
 Define enterprise conceptual data model:
 </li>
 <li>
 Assets, Inventory, Work Orders, Suppliers, Workforce, Technical Docs
 </li>
 <li>
 Establish:
 </li>
 <li>
 Entity relationships
 </li>
 <li>
 Master data definitions
 </li>
 <li>
 Data standardization rules
 </li>
 <li>
 Support BI teams for dashboards and analytics
 </li>
 <li>
 Align data models with business workflows
 </li>
 <li>
 Ensure requirements are data-feasible and consistent
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Required Skills &amp; Experience
 
 
 </li>
 </ul>
 
 Mandatory
 
 
 
 <ul>
 <li>
 5 - 8 years in Data Analyst / Data Architecture roles
 </li>
 <li>
 Experience in large-scale ERP or enterprise data transformation programs
 </li>
 <li>
 Strong expertise in:
 </li>
 <li>
 Data modelling (conceptual &amp; logical)
 </li>
 <li>
 Data migration and cleansing
 </li>
 <li>
 Data warehousing and reporting
 
 
 </li>
 </ul>
 
 Technical Expertise
 
 
 
 <ul>
 <li>
 Strong knowledge of:
 </li>
 <li>
 ETL processes and migration tools
 </li>
 <li>
 SQL and relational databases
 </li>
 <li>
 API-based integrations
 </li>
 <li>
 Experience with BI tools (Power BI, Tableau)
 
 
 </li>
 </ul>
 
 Preferred
 
 
 
 <ul>
 <li>
 Experience in ERP &amp; Enterprise Data Management (logistics, manufacturing)
 </li>
 <li>
 Exposure to:
 </li>
 <li>
 Maintenance (MRO) data
 </li>
 <li>
 Inventory systems
 </li>
 <li>
 Technical documentation repositories
 </li>
 <li>
 Demonstrated experience using AI/ML tools or platforms, such as:
 </li>
 <li>
 Data analysis and prediction tools
 </li>
 <li>
 AI-assisted data modeling or profiling tools
 </li>
 <li>
 Ability to translate data into AI-driven insights for decision-making
 
 
 </li>
 </ul>
 
 Why Join CodeNinja?
 
 
 
 <ul>
 <li>
 Work on impactful ERP transformation projects at enterprise scale
 </li>
 <li>
 Shape end-to-end data strategy, migration, and architecture
 </li>
 <li>
 Leverage AI/ML for advanced data insights and analytics
 </li>
 <li>
 Collaborate with cross-functional teams and drive business decisions
 </li>
 <li>
 Build scalable data models and governance frameworks
 </li>
 <li>
 Grow in a culture of innovation, ownership, and continuous learning
 
 
 </li>
 </ul>
 
 Equal Opportunity Statement
 
 
 
 We are an equal opportunity employer and are committed to fostering an inclusive, diverse, and equitable workplace. We do not discriminate based on race, religion, gender, age, disability, nationality, marital status, or any other protected characteristic under applicable law. We encourage candidates from all backgrounds to apply.
 
 
 
 Benefits
 
 
 
 <ul>
 <li>
 Provident Fund
 </li>
 <li>
 Gym Membership
 </li>
 <li>
 Leaves as per the company policy
 </li>
 <li>
 Company-paid trips
 </li>
 <li>
 Easy Loan Facility for Employees
 </li>
 <li>
 Yearly increment
 </li>
 <li>
 Maternity Benefits (Leaves &amp; WFH)
 </li>
 <li>
 Health Insurance (Maternity covered) - includes spouse and parents (till age 80)
 </li>
 </ul>
</div>

Explore 498+ Big data engineer in Lahore this April. Find roles across top companies and apply now to boost your career.

498 big data engineer jobs In Lahore

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Data Engineer

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Senior Data Engineer

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Data Analyst/Data Architect