Qureos Mentor

Datamatics Technologies

<div>
 
 Job Title: Data Engineer
 
 
 
 Experience:
 
 3&ndash;5 Years
 
 
 Location:
 
 Remote
 
 
 
 
 Only CV matching with JD will be Shortlisted
 
 
 
 
 Role Purpose
 
 
 We are looking for a skilled
 
 Data Engineer
 
 to design, build, and maintain scalable data pipelines within the Azure ecosystem. You will play a key role in enabling data-driven insights by developing reliable data solutions that support analytics, reporting, and business intelligence initiatives.
 
 
 Key Responsibilities
 
 <ul>
 <li>
 Develop and maintain
 
 ETL/ELT pipelines
 
 using
 
 Azure Data Factory (ADF)
 
 </li>
 <li>
 Work with
 
 Azure Data Lake Storage (ADLS)
 
 for data ingestion, storage, and processing
 </li>
 <li>
 Build and optimize data transformations using
 
 PySpark
 
 and
 
 SQL
 
 </li>
 <li>
 Integrate data from multiple structured and unstructured sources
 </li>
 <li>
 Ensure
 
 data quality, integrity, and consistency
 
 across pipelines
 </li>
 <li>
 Support implementation of
 
 Lakehouse architecture
 
 and
 
 Medallion (Bronze, Silver, Gold) layers
 
 </li>
 <li>
 Collaborate with analysts and BI teams to enable reporting and data models
 </li>
 <li>
 Monitor, troubleshoot, and resolve data pipeline issues
 </li>
 <li>
 Document data processes, workflows, and pipeline logic
 </li>
 </ul>
 
 Required Skills &amp; Experience (3&ndash;5 Years)
 
 <ul>
 <li>
 Hands-on experience with
 
 Azure Data Factory (ADF)
 
 and
 
 ADLS
 
 </li>
 <li>
 Strong programming skills in
 
 PySpark
 
 and
 
 SQL
 
 </li>
 <li>
 Experience in building and maintaining
 
 ETL pipelines
 
 </li>
 <li>
 Working knowledge of
 
 structured and unstructured data processing
 
 </li>
 <li>
 Basic understanding of
 
 Lakehouse architecture
 
 and
 
 Medallion framework
 
 </li>
 <li>
 Familiarity with
 
 Delta Lake concepts
 
 </li>
 <li>
 Strong
 
 problem-solving and debugging
 
 skills
 </li>
 </ul>
 
 Preferred Qualifications
 
 <ul>
 <li>
 Experience with
 
 Azure Databricks
 
 </li>
 <li>
 Understanding of
 
 data modeling and data warehousing concepts
 
 </li>
 <li>
 Exposure to
 
 data governance and data quality frameworks
 
 </li>
 <li>
 Experience working in
 
 Agile/Scrum environments
 
 </li>
 </ul>
 
 Soft Skills
 
 <ul>
 <li>
 Strong communication and stakeholder collaboration skills
 </li>
 <li>
 Analytical mindset with attention to detail
 </li>
 <li>
 Ability to work independently in a
 
 remote setup
 
 </li>
 <li>
 Team player with a proactive approach to problem-solving
 </li>
 </ul>
 
 Career Progression Opportunity
 
 
 This role provides a pathway to grow into a
 
 Senior Data Engineer (5&ndash;10 Years)
 
 position, where responsibilities include:
 
 <ul>
 <li>
 Designing end-to-end data architectures
 </li>
 <li>
 Working extensively with
 
 Microsoft Fabric
 
 and advanced Azure services
 </li>
 <li>
 Leading data engineering initiatives and mentoring team members
 </li>
 <li>
 Optimizing large-scale distributed data systems
 </li>
 </ul>
</div>

Data Engineer

<div>
 
 Role Overview
 
 
 Datamatics is seeking a highly motivated
 
 AI Engineer
 
 with a strong focus on designing, developing, and deploying production-grade
 
 LLM-powered applications
 
 . The ideal candidate will have hands-on experience with modern GenAI frameworks such as LangChain and LangGraph, and a deep understanding of Retrieval-Augmented Generation (RAG) architectures.
 
 
 Key Responsibilities
 
 
 AI Application Development
 
 <ul>
 <li>
 Design, develop, and deploy scalable AI applications using Python and modern GenAI frameworks (e.g., LangChain, LangGraph, LlamaIndex)
 </li>
 <li>
 Build production-ready LLM applications for real-world use cases across public health and enterprise domains
 </li>
 <li>
 Integrate state-of-the-art generative AI models to enhance product capabilities and consulting offerings
 </li>
 </ul>
 
 RAG &amp; NLP Engineering
 
 <ul>
 <li>
 Develop and optimize
 
 Retrieval-Augmented Generation (RAG)
 
 pipelines using advanced techniques such as:
 <ul>
 <li>
 Semantic search
 </li>
 <li>
 Hybrid search
 </li>
 <li>
 Re-ranking strategies
 </li>
 </ul>
 </li>
 <li>
 Apply NLP concepts including embeddings, Named Entity Recognition (NER), and text processing to improve model performance
 </li>
 <li>
 Fine-tune retrieval and generation strategies for accuracy, latency, and scalability
 </li>
 </ul>
 
 Architecture &amp; Scalability
 
 <ul>
 <li>
 Collaborate with Data Engineers and Data Scientists to design scalable, high-performance AI solutions
 </li>
 <li>
 Ensure smooth productionization of AI models in collaboration with MLOps teams
 </li>
 <li>
 Deploy and manage AI services using Kubernetes and containerization technologies
 </li>
 <li>
 Work with cloud platforms (AWS, Azure, or GCP) and big data ecosystems
 </li>
 </ul>
 
 Innovation &amp; Continuous Learning
 
 <ul>
 <li>
 Stay updated with the latest advancements in AI, LLMs, and NLP
 </li>
 <li>
 Contribute to innovation by experimenting with emerging tools, frameworks, and methodologies
 </li>
 <li>
 Drive adoption of best practices in AI engineering and system design
 </li>
 </ul>
 
 Required Qualifications
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Engineering, Data Science, or a related field (with focus on AI/ML/NLP)
 </li>
 <li>
 1&ndash;3 years of hands-on experience in AI/ML application development
 </li>
 <li>
 Strong programming skills in Python
 </li>
 </ul>
 
 Required Skills
 
 <ul>
 <li>
 Experience with GenAI frameworks such as LangChain, LangGraph, and/or LlamaIndex
 </li>
 <li>
 Strong understanding of:
 <ul>
 <li>
 LLMs and prompt engineering
 </li>
 <li>
 RAG architectures
 </li>
 <li>
 Embeddings and vector databases
 </li>
 </ul>
 </li>
 <li>
 Familiarity with NLP techniques such as NER, semantic search, and text processing
 </li>
 <li>
 Experience with:
 <ul>
 <li>
 Kubernetes and containerization (Docker)
 </li>
 <li>
 Cloud platforms (AWS, Azure, or GCP)
 </li>
 <li>
 Big data tools (e.g., Apache Spark) and data lake architectures
 </li>
 </ul>
 </li>
 <li>
 Strong problem-solving, analytical thinking, and communication skills
 </li>
 </ul>
 
 Preferred Qualifications
 
 <ul>
 <li>
 Experience building production-grade AI/LLM applications
 </li>
 <li>
 Exposure to MLOps practices and model lifecycle management
 </li>
 <li>
 Familiarity with vector databases (e.g., Pinecone, FAISS, Weaviate)
 </li>
 <li>
 Understanding of scalable system design and microservices architecture
 </li>
 </ul>
</div>

AI Engineer

<div>
 
 Job Title: Big Data Engineer
 
 Expericence - 5 to 8 Years -
 
 
 
 CV with relevant skills will be contacted.
 
 
 
 Role Purpose
 
 
 The Big Data Engineer is responsible for designing, developing, and maintaining scalable data pipelines and distributed data processing systems. This role enables efficient data ingestion, transformation, and analytics across batch and real-time environments, supporting enterprise-wide data initiatives.
 
 
 Key Responsibilities
 
 <ul>
 <li>
 Design, develop, and maintain scalable
 
 batch and real-time data pipelines
 
 to support analytics and business intelligence use cases
 </li>
 <li>
 Build and manage distributed data processing solutions using
 
 Apache Hadoop
 
 and
 
 Apache Spark
 
 within
 
 Cloudera Data Platform (CDP)
 
 </li>
 <li>
 Develop and orchestrate
 
 ETL workflows
 
 using tools such as
 
 Apache NiFi
 
 </li>
 <li>
 Implement and manage
 
 real-time streaming pipelines
 
 using
 
 Apache Kafka
 
 </li>
 <li>
 Work with distributed storage systems such as
 
 Hadoop Distributed File System (HDFS)
 
 </li>
 <li>
 Utilize query engines like
 
 Apache Hive
 
 and
 
 Apache Impala
 
 for data access and analytics
 </li>
 <li>
 Perform
 
 data ingestion, transformation, and integration
 
 from multiple structured and unstructured enterprise data sources
 </li>
 <li>
 Optimize data pipelines for
 
 performance, scalability, and reliability
 
 </li>
 <li>
 Monitor and troubleshoot data workflows, ensuring high availability and data integrity
 </li>
 <li>
 Collaborate closely with
 
 data architects, analysts, and business stakeholders
 
 to deliver data solutions aligned with business needs
 </li>
 <li>
 Ensure adherence to
 
 data governance, security, and data quality standards
 
 </li>
 <li>
 Document data processes, architectures, and workflows for operational efficiency
 </li>
 </ul>
 
 Required Skills &amp; Experience
 
 <ul>
 <li>
 
 5&ndash;8 years
 
 of experience in Big Data Engineering or related roles
 </li>
 <li>
 Strong hands-on experience with:
 <ul>
 <li>
 Apache Hadoop ecosystem
 </li>
 <li>
 Apache Spark (PySpark/Scala preferred)
 </li>
 <li>
 Apache Kafka (streaming)
 </li>
 <li>
 Apache NiFi (data ingestion/ETL)
 </li>
 </ul>
 </li>
 <li>
 Experience with
 
 Cloudera Data Platform (CDP)
 
 or similar big data platforms
 </li>
 <li>
 Proficiency in
 
 SQL
 
 and at least one programming language (Python, Scala, or Java)
 </li>
 <li>
 Solid understanding of
 
 distributed computing and parallel processing concepts
 
 </li>
 <li>
 Experience working with
 
 HDFS, Hive, and Impala
 
 </li>
 <li>
 Knowledge of
 
 data modeling, ETL design, and data warehousing concepts
 
 </li>
 <li>
 Familiarity with
 
 data governance, security, and compliance frameworks
 
 </li>
 <li>
 Strong problem-solving and performance tuning skills
 </li>
 </ul>
 
 Preferred Qualifications
 
 <ul>
 <li>
 Experience with
 
 cloud platforms
 
 (AWS, Azure, or GCP) in big data environments
 </li>
 <li>
 Knowledge of
 
 containerization (Docker/Kubernetes)
 
 is a plus
 </li>
 <li>
 Exposure to
 
 CI/CD pipelines
 
 for data engineering workflows
 </li>
 <li>
 Understanding of
 
 real-time analytics and event-driven architectures
 
 </li>
 </ul>
 
 Key Competencies
 
 <ul>
 <li>
 Analytical thinking and problem-solving
 </li>
 <li>
 Strong collaboration and communication skills
 </li>
 <li>
 Ability to work in fast-paced, data-driven environments
 </li>
 <li>
 Attention to detail and commitment to data quality
 </li>
 </ul>
 
 Education
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in
 
 Computer Science, Information Technology, Data Engineering
 
 , or a related field
 </li>
 </ul>
</div>

Big Data Engineer

<div>
 
 DevOps Consultant -SDLC
 
 
 CV should be as per JD
 
 
 
 Experience:
 
 7&ndash;10 Years
 
 
 Location
 
 : Riyadh - KSA
 
 
 Role Purpose
 
 
 Act as a strategic consultant to optimize SDLC processes, DevOps practices, and toolchain integration, ensuring efficient and streamlined delivery pipelines.
 
 
 Key Responsibilities
 
 <ul>
 <li>
 Assess and improve existing SDLC and DevOps processes
 </li>
 <li>
 Provide consultancy on best practices for CI/CD, version control, and release management
 </li>
 <li>
 Work closely with teams using tools like GitLab, Jira, and related platforms
 </li>
 <li>
 Define and implement DevOps governance frameworks and workflows
 </li>
 <li>
 Facilitate collaboration between development, QA, and operations teams
 </li>
 <li>
 Recommend automation strategies and process improvements
 </li>
 <li>
 Support Agile transformation and DevOps maturity initiatives
 </li>
 <li>
 Conduct workshops and training sessions for teams
 </li>
 </ul>
 
 Required Skills
 
 <ul>
 <li>
 Strong understanding of SDLC methodologies and DevOps principles
 </li>
 <li>
 Hands-on experience with tools like GitLab, Jira, Confluence, Jenkins (functional level expected)
 </li>
 <li>
 Experience in CI/CD pipeline design and optimization
 </li>
 <li>
 Knowledge of Agile and Scrum frameworks
 </li>
 <li>
 Strong consulting, communication, and stakeholder management skills
 </li>
 <li>
 Ability to work at a strategic level rather than deep technical execution
 </li>
 </ul>
</div>

DevOps Consultant - SDLC

<div>
 
 BA/BI Consultant (Onshore)
 
 
 
 Contractual Role - 4 Months
 
 
 Role Purpose
 
 
 Act as the key interface between business stakeholders and the delivery team, leveraging strong finance domain expertise to gather requirements, define reporting logic, and translate business and financial needs into actionable BI solutions.
 
 
 Key Responsibilities
 
 <ul>
 <li>
 Conduct requirement gathering workshops with business and finance stakeholders (FP&amp;A, Accounting, Reporting teams)
 </li>
 <li>
 Document detailed business and financial requirements, including KPIs, metrics, and analytical use cases
 </li>
 <li>
 Define financial data requirements, including ratios, measures, and reporting logic
 </li>
 <li>
 Prepare comprehensive functional specifications for dashboards and financial reports
 </li>
 <li>
 Define data mappings, business rules, and financial transformations for ETL processes
 </li>
 <li>
 Collaborate with data engineering and BI teams to ensure accurate implementation of financial logic
 </li>
 <li>
 Enable self-service BI and ad-hoc reporting capabilities with proper governance and access controls
 </li>
 <li>
 Act as a bridge between onshore stakeholders and offshore delivery teams for clarifications and alignment
 </li>
 <li>
 Support and coordinate
 
 User Acceptance Testing (UAT)
 
 with finance users, ensuring business validation and sign-off
 </li>
 <li>
 Ensure consistency, accuracy, and integrity of financial data across reports
 </li>
 </ul>
 
 Required Skills &amp; Qualifications
 
 <ul>
 <li>
 Strong experience in
 
 Business Analysis
 
 with deep expertise in the
 
 Finance domain (FP&amp;A, Accounting, Financial Reporting)
 
 </li>
 <li>
 In-depth understanding of financial KPIs, ratios, and performance metrics
 </li>
 <li>
 Proven experience in
 
 Actual vs Budget vs Forecast
 
 , variance analysis, and trend analysis
 </li>
 <li>
 Solid knowledge of financial statements:
 
 P&amp;L, Balance Sheet, and Cash Flow
 
 </li>
 <li>
 Understanding of
 
 General Ledger (GL)
 
 structures and financial data flows
 </li>
 <li>
 Good knowledge of
 
 data modelling, ETL processes, and financial data transformations
 
 </li>
 <li>
 Familiarity with
 
 Oracle Analytics Cloud (OAC)
 
 or similar BI/reporting tools
 </li>
 <li>
 Excellent stakeholder management and communication skills, especially with senior finance stakeholders (e.g., CFO, FP&amp;A leadership)
 </li>
 <li>
 Ability to conduct workshops and translate complex financial concepts into clear BI requirements
 </li>
 </ul>
 
 Preferred Skills
 
 <ul>
 <li>
 Experience in banking or financial services domain
 </li>
 <li>
 Exposure to data warehousing concepts and BI architecture
 </li>
 <li>
 Experience working in Agile/Scrum environments
 </li>
 </ul>
 
 Engagement Details
 
 <ul>
 <li>
 
 Location:
 
 Onshore
 </li>
 <li>
 
 Type:
 
 Contract / Project-based (can be adjusted as per requirement)
 </li>
 <li>
 
 Stakeholders:
 
 Finance Leadership, FP&amp;A Teams, Data &amp; BI Teams
 </li>
 </ul>
</div>

BA/BI Consultant

<div>
 
 
 
 
 Job Title:
 
 Utility Industry Consultant (Domain SME)
 
 
 
 
 
 
 
 
 Location:
 
 Hybrid
 
 
 
 
 
 
 
 
 Employment Type:
 
 Contract
 
 
 
 
 
 
 
 
 Experience Level:
 
 Senior (7+ years in Utilities)
 
 
 
 
 
 
 
 
 
 Role Overview
 
 
 
 
 
 
 
 
 We are seeking a specialized Utility Industry Consultant to act as the bridge between business stakeholders (Operations, Finance, Asset Management) and the technical development team. The primary mission is to identify, define, and operationalize high-value Key Performance Indicators (KPIs) specific to the utility sector.
 
 
 
 
 
 
 
 Unlike a standard data analyst, this candidate must understand
 
 why
 
 certain metrics matter (regulatory, safety, reliability) and translate that logic into precise business rules for developers.
 
 
 
 
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 <ul>
 <li>
 
 
 
 
 
 
 Identify high-value utility KPIs
 
 
 
 
 
 (reliability, operational, financial, customer, grid modernization) through stakeholder workshops.
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Define business rules
 
 
 
 
 
 for each KPI: numerators/denominators, filters (e.g., exclude major events), temporal logic, and aggregation hierarchies.
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Translate rules into technical specs
 
 
 
 
 
 (pseudo-code, decision tables, mapping docs) for data engineers and BI developers.
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Validate KPI logic
 
 
 
 
 
 by reviewing testing outputs, and leading UAT with utility subject matter experts.
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Document KPI dictionary
 
 
 
 
 
 and support change management / internal training.
 
 
 
 
 
 </li>
 </ul>
 
 
 
 
 Required Qualifications
 
 
 
 
 
 
 
 
 
 Domain Expertise
 
 
 
 
 <ul>
 <li>
 
 
 
 7+ years working in or consulting for
 
 Electric, Gas, or Water utilities
 
 .
 
 
 
 </li>
 <li>
 
 
 
 Deep understanding of utility data sources:
 
 SCADA, ADMS/OMS, GIS, CIS, EAM (Maximo/SAP), Smart Meters (AMI)
 
 .
 
 
 
 </li>
 <li>
 
 
 
 Fluency in utility regulatory frameworks (NERC CIP, FERC, RTO/ISO market rules, or local PUC standards).
 
 
 
 </li>
 </ul>
 
 
 
 
 KPI &amp; Analytical Skills
 
 
 
 
 <ul>
 <li>
 
 
 
 Proven track record of defining operational KPIs for:
 
 
 
 <ul>
 <li>
 
 
 
 
 Reliability
 
 (SAIDI, SAIFI, CAIDI, MAIFI)
 
 
 
 </li>
 <li>
 
 
 
 
 Operational Excellence
 
 (Crew ETA accuracy, First-time fix rate)
 
 
 
 </li>
 <li>
 
 
 
 
 Customer
 
 (Average speed to answer, Call abandonment rate)
 
 
 
 </li>
 <li>
 
 
 
 
 Financial
 
 (Bad debt %, Rate case metrics)
 
 
 
 </li>
 <li>
 
 
 
 
 Grid Modernization
 
 (DER hosting capacity utilization, Volt/VAR optimization success).
 
 
 
 </li>
 </ul>
 </li>
 <li>
 
 
 
 Ability to differentiate between a "lagging" and "leading" indicator for utilities.
 
 
 
 </li>
 <li>
 
 
 
 Experience writing detailed Business Rules Documents (BRDs) or User Stories (e.g., "Given, When, Then" formats).
 
 
 
 
 </li>
 </ul>
 
 
 
 
 Soft Skills
 
 
 
 
 <ul>
 <li>
 
 
 
 Exceptional facilitation skills to mediate between a lineman (field) and a data architect (IT).
 
 
 
 </li>
 <li>
 
 
 
 Conflict resolution: "Why doesn't the KPI match my spreadsheet?" scenarios are common.
 
 
 
 </li>
 </ul>
 
 
 
 
 Nice to Have (Differentiators)
 
 
 
 
 <ul>
 <li>
 
 
 
 Experience with
 
 Utility-specific BI tools
 
 (e.g., OSIsoft PI Vision, GE Digital APM, Oracle Utilities Opower).
 
 
 
 </li>
 <li>
 
 
 
 Knowledge of
 
 ISO 55000
 
 (Asset Management) or
 
 WEF
 
 (Water) standards.
 
 
 
 </li>
 <li>
 
 
 
 Previous role as a Utility Data Steward or Business Analyst in a large IOU (Investor-Owned Utility) or Co-op.
 
 
 
 </li>
 </ul>
</div>

Utility Industry Consultant

Join Datamatics Technologies and explore 11   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

Datamatics Technologies

About Company

Data Engineer

Data Engineer

AI Engineer

Big Data Engineer

DevOps Consultant - SDLC

BA/BI Consultant

Utility Industry Consultant