aws data engineer

CrossAsyst

<div><div>AWS Data Engineer (ETL Specialist)</div><div>
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Experience: 3-5 years (minimum 2+ years hands-on experience with AWS-native data engineering tools)</div><div></div><div> 
Location: Gigaplex, Airoli West</div><div>
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Role Overview: The AWS Data Engineer will design, develop, and manage scalable data pipelines and analytics infrastructure in a cloud-native environment. This engineer will be responsible for architecting complex ETL processes using AWS-managed services, optimizing data performance, and ensuring data quality, security, and observability across multiple systems. The ideal candidate has deep AWS knowledge, strong ETL design experience, and a solid grasp of modern data engineering practices.</div><div>
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Key Responsibilities:</div><ul><li>Design and implement end-to-end ETL workflows leveraging AWS services such as Glue, Lambda, Step Functions, EMR, Redshift, Kinesis, and S3.</li><li>Develop and maintain data ingestion pipelines from structured, semi-structured, and streaming data sources.</li><li>Design and maintain data lake and data warehouse solutions (S3, Redshift, Lake Formation).</li><li>Build transformation logic with PySpark, SQL, or Python, ensuring performance and integrity.</li><li>Orchestrate workflows using AWS Glue Workflows, Apache Airflow, or Step Functions.</li><li>Implement data quality validations, monitoring frameworks, and automated alerts for pipeline health.</li><li>Collaborate with data scientists, analysts, and application engineering teams to ensure data accessibility and alignment with analytics use cases.</li><li>Ensure compliance with data governance and security frameworks (IAM, encryption, GDPR/HIPAA as applicable).</li><li>Participate in data architecture reviews, contributing to design best practices for reliability and scalability.</li><li>Document all data flows, transformations, and pipeline specifications for reproducibility and audits.</li></ul><div>
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Required Technical Skills:</div><ul><li>Strong development background in Python and SQL.</li><li>Expertise with AWS data services: Glue, Redshift, EMR, S3, RDS, Lambda, Kinesis, CloudWatch, and CloudFormation.</li><li>Deep understanding of ETL/ELT design patterns, including incremental loads and change data capture (CDC).</li><li>Familiarity with data modelling (Star/Snowflake schemas) and data lakehouse architectures.</li><li>Experience working with large-scale or real-time datasets.</li><li>Knowledge of data quality frameworks and data observability tools.</li><li>Comfort with DevOps and CI/CD workflows using Git, CodePipeline, or Terraform.</li><li>Advanced understanding of data security practices in AWS (IAM roles, encryption, network isolation).</li></ul><div>
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Desired Skills:</div><ul><li>Hands-on experience with Snowflake, Databricks, or Athena.</li><li>Familiarity with BI/analytics tools (QuickSight, Power BI, Tableau).</li><li>AWS certifications such as AWS Certified Data Engineer &ndash; Associate or Data Analytics Specialty.</li><li>Strong analytical and communication skills to translate business data needs into engineering solutions.</li></ul><div>
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Educational Requirements:</div><ul><li>Master's or Bachelor&rsquo;s degree in Computer Science, Data Engineering, or related technical field.</li><li>AWS Data Engineering or Data Analytics certification preferred</li></ul></div>

AWS Data Engineer

HireWand Technologies

The AWS Data Engineer will design, develop, and maintain scalable data pipelines and architectures using AWS Glue, Amazon Redshift, AWS Lambda, and Amazon S3. This role requires expertise in AWS Kinesis, AWS CloudFormation, Apache Spark, Python, and AWS IAM to ensure secure and efficient data processing. The candidate will leverage AWS Data Pipeline, AWS Athena, Docker, Terraform, and Apache Airflow to automate workflows and optimize data integration. Proficiency in AWS CloudWatch, Scala, SQL, PySpark, CI/CD, and DevOps practices is essential for monitoring and continuous improvement.
 
Strong problem-solving skills and critical thinking will drive innovative solutions to complex data challenges. Effective communication and collaboration are vital for working with cross-functional teams and stakeholders. Attention to detail and time management will ensure timely delivery of high-quality data solutions. Adaptability and project management skills will support evolving business needs and technology landscapes.
 
Responsibilities: Demonstrate expert knowledge in AWS Glue, Amazon Redshift, AWS Lambda, Amazon S3, and Apache Spark to build and optimize data solutions. Design, implement, and maintain robust data pipelines and ETL processes using AWS Data Pipeline, Apache Airflow, and Python to support analytics and reporting. Develop infrastructure as code using AWS CloudFormation and Terraform to automate deployment and ensure scalable cloud environments. Monitor data workflows and system performance with AWS CloudWatch and implement CI/CD pipelines to enhance deployment efficiency and reliability.
 
Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver actionable insights. Apply best practices in AWS IAM for secure access control and compliance across data platforms and services. Manage containerized applications using Docker and integrate DevOps methodologies to streamline development and operational processes. Qualifications: Bachelor's degree in Computer Science, Information Technology, or a related field is required.,Candidates must have 5-8 years of professional experience in data engineering with a focus on AWS technologies.,Proven experience in designing and managing cloud-based data infrastructure and pipelines is essential.
 
We invite skilled AWS Data Engineers with 5-8 years of experience and expertise in AWS Glue, Redshift, Lambda, and related technologies to join our team. Candidates should excel in problem solving, effective communication, and project management to drive innovative data solutions in a collaborative and dynamic environment.

Mentruiter

Job PurposeDesign, develop, enhance, and integrate an enterprise data warehouse and support AWS cloud infrastructure. Complete projects, prioritize tasks, and provide frequent progress reports with little to no assistance from team leads based on company needs. Responsible for implementing scalable solutions that align with our data governance standards and architectural roadmap for data integrations, data storage, reporting, and analytic solutions.Responsibilities and DutiesThe following statements describe the general nature and level of work being performed by people assigned to this classification. These are not to be construed as an exhaustive list of all job duties.1. Build and support components and infrastructures of the data warehouse in Amazon Redshift. Develop ETL/ELT jobs in Matillion that gather and process raw data from multiple disparate sources (including SQL, text files, JSON, and APIs) into a form suitable for data warehousing, data marts, models, reports, and machine learning. Maintain and create AWS Lambda functions using Python. 2. Support the hands-on technical delivery of services and capabilities within the AWS environment; Manage the AWS Cloud infrastructure, in particular, compute and storage services (EC2, S3), identify and troubleshoot faults, and provide recommendations to ensure proper utilization. 3. Gather and interpret ongoing business requirements; research required data. Collaborate with Business stakeholders, Subject Matter Experts, and the Quality Assurance team to ensure valid and proper deliverables. 4. Participate in Data Quality initiatives and lead the data transformation component design to improve and maintain high-quality data. Support performance tuning and design for optimal system performance for large volumes of data. 5. Code and write unit/functional tests for new or modified data systems 6. Create supporting technical and functional documentation, including data flow diagrams, and provide support for the existing data dictionaries and metadata tables for managing data. Explain tasks and processes clearly and concisely that can be consumed and understood by non-technical business associates. 7. Assists knowledge sharing and mentoring other employees with fewer skill sets to promote best practices and foster growth. 8. Acts as a stand-in for the team lead on projects and meetings when necessary. Complete code reviews of other team members. 9. Supports business decisions with ad-hoc analysis as needed. 10. Participate in the rotation of after-hours support. 11. Additional duties and responsibilities may be assigned.Education and Qualifications1. Bachelor&rsquo;s degree in a related discipline (Computer Science, Information Systems Management, Engineering, or similar) or equivalent work experience. 2. 3+ years of experience implementing on-premise or cloud-based data lake/data warehouse technologies in Redshift. 3. 3+ years of experience working with high-volume data and building batch and near real-time ETL processes 4. 3+ years of experience with AWS Cloud services such as EC2, S3, Lambda, and API Gateway. 5. Understand general concepts of data modeling. 6. Experience SQL Server and reporting solutions such as SSRS (Reporting Services)/Power BI Dashboards. 7. Ability to quickly identify and troubleshoot problematic faults in data pipelines and infrastructure. 8. Ability to design tables, models, data marts, and/or databases to suit business needs. 9. Knowledge of data mapping, data integration, database design and data warehouse concepts. 10. Experience using Jira, Bitbucket, and GitKraken with a good understanding of Git. 11. Desire and ability to learn emerging technologies and methodologies. 12. Ability to interpret requests and requirements to build appropriate automated solutions. 13. Ability to work with shifting deadlines in a fast-paced environment. 14. Strong computer skills including Microsoft Office (Visio, Excel, Word, &amp; Outlook). 15. Strong attention to detail, interpersonal skills, and notation skills.Job Type: Full-timePay: Rs250,000.00 - Rs300,000.00 per monthWork Location: Remote

AWS Data Engineer (Healthcare)

<div>Line of Service
Advisory
Industry/Sector
Technology
Specialism
Advisory - Other
Management Level
Senior Associate
Job Description &amp; Summary
As a Senior Associate in the Data Engineering team, you will play a key role in designing, building, and optimizing modern data platforms and pipelines on AWS. You will work within cross-functional teams to deliver scalable, secure, and high-performing data solutions that enable advanced analytics, AI, and business insights for enterprise clients.
 
This role requires a strong understanding of cloud data architecture and hands-on experience with AWS data services for batch and real-time data engineering.
<h3 class="jobSectionHeader">Key Responsibilities
</h3><ul><li>Design, develop, and maintain end-to-end data pipelines across structured, semi-structured, and unstructured data sources.
</li><li>Implement data ingestion, transformation, and orchestration frameworks leveraging AWS Glue, Amazon Redshift, AWS Step Functions, and Amazon Managed Workflows for Apache Airflow (MWAA) .
</li><li>Develop and optimize ETL/ELT processes using PySpark, SQL, and Delta Lake to ensure high performance and scalability.
</li><li>Implement and enforce data quality, lineage, and governance practices.
</li><li>Work closely with solution architects to design modern data architectures and ensure compliance with security and privacy standards.
</li><li>Participate in client workshops and technical discussions to translate business needs into technical designs.
</li></ul><h3 class="jobSectionHeader">Required Skills &amp; Experience
</h3><ul><li>3&ndash;6 years of experience in data engineering, preferably in a consulting or enterprise environment.
</li><li>Strong hands-on experience with:
<ul><li>AWS Data Platform : AWS Glue, Amazon Redshift, Amazon S3, AWS Lambda, Amazon Kinesis, and AWS Step Functions.
</li></ul></li><li>Proficiency in Python and SQL for large-scale data processing and transformation.
</li><li>Solid understanding of data modeling, medallion architecture, and lakehouse principles.
</li><li>Familiarity with CI/CD pipelines, DevOps, and version control (e.g., Git, AWS CodePipeline).
</li><li>Knowledge of data governance, lineage, and observability tools.
</li><li>Experience with performance optimization, cost control, and best practices in cloud environments.
</li></ul>Education (if blank, degree and/or field of study not specified)
Degrees/Field of Study required:
Degrees/Field of Study preferred:
Certifications (if blank, certifications not specified)
Required Skills
Optional Skills
Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Communication, Creativity, Data Anonymization, Data Architecture, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline {+ 27 more}
Desired Languages (If blank, desired languages not specified)
Travel Requirements
Not Specified
Available for Work Visa Sponsorship?
No
Government Clearance Required?
No
Job Posting End Date</div>

ETIC, AWS Data Engineer, Senior Associate

Quadrabay Verification Services

Position SummaryWe are seeking a skilled Data Engineer with strong expertise in building and managing ETL/ELT pipelines using PySpark within an AWS cloud environment. The ideal candidate will be responsible for designing, implementing, and maintaining scalable data workflows to support multiple data sources, while ensuring seamless integration with Power BI for reconciliation, reporting, and advanced analytics.Key Responsibilities&middot; Data Pipeline Developmento Design, develop, and maintain scalable ETL/ELT pipelines using PySpark.o Implement data ingestion from multiple data sources (Finance, CRM, Payment Gateways, etc.) into AWS Data Lake/Warehouse.o Ensure efficient data partitioning, schema management, and optimization for large datasets.&middot; Cloud &amp; Infrastructure (AWS)o Leverage AWS services (S3, Glue, EMR, Redshift, Lambda, Step Functions) for data engineering workflows.o Implement data security, access control, and compliance in line with organizational standards.o Automate deployments using CI/CD pipelines.&middot; Data Integration &amp; Reportingo Prepare curated datasets for Power BI dashboards and reports.o Enable reconciliation processes by providing granular, auditable datasets.o Collaborate with BI developers to ensure data accuracy, integrity, and performance in reporting.&middot; Collaboration &amp; Processo Work closely with Business Analysts, Data Scientists, and ERP functional teams to understand requirements.o Participate in data governance initiatives, ensuring metadata, lineage, and quality controls are implemented.o Provide support for ad-hoc analytics requests from stakeholders.Required Skills &amp; Qualifications&middot; Technical Skillso Strong programming in Python with deep knowledge of PySpark.o Proven experience in ETL/ELT pipeline development in distributed environments.o Expertise in AWS data services (S3, Glue, EMR, Redshift, Athena, Lambda, Kinesis).o Proficiency in SQL (analytical queries, optimization, tuning).o Familiarity with Power BI integration (Direct Query, Dataflows, Gateways).&middot; Data Engineering Practiceso Experience with data lakes, warehouses, and star/snowflake schema design.o Knowledge of data quality frameworks, reconciliation processes, and auditability controls.o Hands-on experience with workflow orchestration tools.&middot; Soft Skillso Strong problem-solving and analytical skills.o Ability to collaborate across IT, business, and analytics teams.o Clear communication for technical and non-technical stakeholders.Preferred Qualifications&middot; Experience with ERP data models (Finance, CRM - Reconciliation).&middot; Exposure to machine learning data preparation (feature engineering, training/test datasets).&middot; Certification(s):o AWS Certified Data Analytics &ndash; Specialtyo Databricks/Spark Developer Certificationo Microsoft Power BI Data Analyst AssociateJob Type: Full-timeAbility to commute/relocate:<ul><li>Ajman: Reliably commute or planning to relocate before starting work (Preferred)</li></ul>Application Question(s):<ul><li>Availability to start immediately </li><li>Visa Status</li></ul>Experience:<ul><li>Data Engineer: 3 years (Preferred)</li></ul>Language:<ul><li>English (Preferred)</li></ul>

Data Engineer

CAI (Computer Aid, Inc.)

Req number: R6413
 
Employment type: Full time
 
Worksite flexibility: Remote Who we are
 CAI is a global technology services firm with over 8,500 associates worldwide and a yearly revenue of $1 billion+. We have over 40 years of excellence in uniting talent and technology to power the possible for our clients, colleagues, and communities. As a privately held company, we have the freedom and focus to do what is right—whatever it takes. Our tailor-made solutions create lasting results across the public and commercial sectors, and we are trailblazers in bringing neurodiversity to the enterprise.
 
Job Summary We are seeking a motivated Data Engineer to join our dynamic team. As a Data Engineer, you will play a crucial role in building cloud-based data lake and analytics architectures using AWS and Databricks and is proficient in Python programming for data processing and automation. This is a Full-time and Remote position.
 
Job Description
 We are looking for a Data Engineer that has experience in building data products using Databricks and related technologies. This position will be Full-time and Remote position.
 What You’ll Do
 
Design, develop, and maintain data lakes and data pipelines on AWS using ETL frameworks and Databricks
 
Integrate and transform large-scale data from multiple heterogeneous sources into a centralized data lake environment
 
Implement and manage Delta Lake architecture using Databricks Delta or Apache Hudi
 
Develop end-to-end data workflows using PySpark, Databricks Notebooks, and Python scripts for ingestion, transformation, and enrichment
 
Design and develop data warehouses and data marts for analytical workloads using Snowflake, Redshift, or similar systems
 
Design and evaluate data models (Star, Snowflake, Flattened) for analytical and transactional systems
 
Optimize data storage, query performance, and cost across the AWS and Databricks ecosystem
 
Build and maintain CI/CD pipelines for Databricks notebooks, jobs, and Python-based data processing scripts
 
Collaborate with data scientists, analysts, and stakeholders to deliver high-performance, reusable data assets
 
Maintain and manage code repositories (Git) and promote best practices in version control, testing, and deployment
 
Participate in making major technical and architectural decisions for data engineering initiatives
 
Monitor and troubleshoot Databricks clusters, Spark jobs, and ETL processes for performance and reliability
 
Coordinate with business and technical teams through all phases of the software development life cycle
 What You'll Need
 Required
 
5+ years of experience building and managing Data Lake Architecture on AWS Cloud
 
3+ years of experience with AWS Data services such as S3, Glue, Lake Formation, EMR, Kinesis, RDS, DMS, and Redshift
 
3+ years of experience building Data Warehouses on Snowflake, Redshift, HANA, Teradata, or Exasol
 
3+ years of hands-on experience working with Apache Spark or PySpark, on Databricks
 
3+ years of experience implementing Delta Lakes using Databricks Delta or Apache Hudi
 
3+ years of experience in ETL development using Databricks, AWS Glue, or other modern frameworks
 
Proficiency in Python for data engineering, automation, and API integrations.
 
Experience in Databricks Jobs, Workflows, and Cluster Management
 
Experience with CI/CD pipelines and Infrastructure as Code (IaC) tools like Terraform or CloudFormation is a plus
 
Bachelor’s degree in computer science, Information Technology, Data Science, or related field
 Physical Demands
 
This role involves mostly sedentary work, with occasional movement around the office to attend meetings, etc.
 
Ability to perform repetitive tasks on a computer, using a mouse, keyboard, and monitor
 
Reasonable accommodation statement
 If you require a reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employment selection process, please direct your inquiries to application.accommodations@cai.io or (888) 824 – 8111.

ATOM Insurance

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 You will be working on projects with teams from across our ATOM Platform and Business Intelligence/Data Science practice. Reporting to the Chief Product Officer, you will deliver digestible, contemporary and immediate data content to support and drive business decisions. The key focus of the role is to deliver reports, dashboards and custom solutions for various business critical requirements. You will be involved in all aspects of data engineering from delivery planning, estimating and analysis, all the way through to data architecture and pipeline design, delivery and production implementation. From day one, you will be involved in the design and implementation of complex data solutions ranging from batch to streaming and event-driven architectures, across cloud, on-premise and hybrid client technology landscapes. As a Data Engineer, you will: Build different types of data warehousing layers based on specific use cases Lead the design, implementation, and successful delivery of large-scale, critical, or difficult data solutions involving a significant amount of work Build scalable data infrastructure and understand distributed systems concepts from a data storage and compute perspective Utilize expertise in SQL and have a strong understanding of ETL and data modeling Ensure the accuracy and availability of data to customers and understand how technical decisions can impact their business s analytics and reporting Be proficient in at least one scripting/programming language to handle large volume data processing We are looking for 5+ years of experience in data engineering in a customer or business facing capacity. 
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 To be considered for this role you will have: Ability to understand and articulate requirements to technical and non-technical audiences Stakeholder management and communication skills, including prioritising, problem solving and interpersonal relationship building Strong experience in SDLC delivery, including waterfall, hybrid and Agile methodologies. Experience delivering in an agile environment Experience of implementing and delivering data solutions and pipelines on AWS Cloud Platform A strong understanding of data modelling, data structures, databases, and ETL processes An in-depth understanding of large-scale data sets, including both structured and unstructured data Strong SQL and Python knowledge Knowledge and experience of delivering CI/CD and DevOps capabilities in a data environment Basic qualifications: At least 3- 5 years of Consulting or client service delivery experience on Amazon AWS (AWS) At least 3- 5 years of experience in developing data ingestion, data processing and analytical pipelines for big data, relational databases, NoSQL and data warehouse solutions Extensive experience providing practical direction within the AWS Native and Hadoop Experience with private and public cloud architectures, pros/cons, and migration considerations Minimum of 5 years of hands-on experience in AWS and Big Data technologies such as Java, Node.js, C##, Python, SQL, EC2, S3, Lambda, Spark/SparkSQL, Hive/MR, Pig, Oozie and streaming technologies such as Kafka, Kinesis, NiFI etc. 3-5+ years of hands on experience in programming languages such as Java, c#, node.js, python, pyspark, spark, SQL, Unix shell/Perl scripting etc. Experience working with DevOps tools such as GitLabs, Jenkins, CodeBuild, CoePipeline CodeDeploy, etc. Bachelors or higher degree in Computer Science or a related discipline Must have at least one AWS certification: Certified AWS Developer Associate Certified AWS DevOps Professional Certified AWS Big Data Specialty Nice-to-have skills/qualifications: DevOps on an AWS platform. Multi-cloud experience a plus Experience developing and deploying ETL solutions on AWS using tools like Talend, Informatica, Matillion Strong in Java, C##, Spark, PySpark, Unix shell/Perl scripting IoT, event-driven, microservices, containers/Kubernetes in the cloud
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