Senior Data Engineer - Remote, Flexible Hours
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Job summary
Endava is seeking a Senior Data Engineer to design, build, and optimize scalable data platforms for high-volume financial and transactional data. You will engineer end-to-end data pipelines, manage cloud data warehouses, and ensure data governance across environments.
Candidates must reside exclusively in Argentina, Brazil, or Uruguay. You will collaborate with Data Scientists, Software Engineers, and Product Managers to deliver robust analytics solutions in a globally distributed context.
Qualifications
- 5+ years in data engineering or related software engineering roles.
- Strong Python and SQL for complex data processing.
- Experience with Airflow, Snowflake, DBT, and AWS.
- CI/CD and Infrastructure-as-Code practices.
Responsibilities
- Design, build, and maintain high-throughput data pipelines for batch and streaming data.
- Develop and optimize cloud data warehouse architectures and data models.
- Mentor junior engineers and participate in technical reviews.
- Implement data quality, monitoring, and governance across platforms.
Skills
Tools
Job description
Our data team has expertise across engineering, analysis, architecture, modeling, machine learning, artificial intelligence, and data science. This discipline is responsible for transforming raw data into actionable insights, building robust data infrastructures, and enabling data-driven decision-making and innovation through advanced analytics and predictive modeling.
As a Data Engineer at Endava you will:
- Design, develop, and maintain scalable ETL/ELT pipelines for data ingestion, transformation, validation, and delivery.
- Develop reusable, modular, and configuration-driven data processing solutions.
- Contribute to technical architecture and evaluate solutions based on scalability, performance, reliability, and maintainability.
- Design and optimize data models, SQL queries, stored procedures, and data processing workflows.
- Design and maintain Apache Airflow workflows, including scheduling, dependencies, retries, monitoring, and error handling.
- Develop automated data validation and quality checks using DBT and SQL.
- Implement appropriate monitoring, alerting, and observability for critical data pipelines.
- Troubleshoot and resolve complex data processing and quality issues.
- Develop data solutions using AWS and cloud-based data warehouse technologies such as Snowflake.
- Work with cloud services for data storage, processing, compute, messaging, and serverless workloads.
- Support data platforms across development, QA, staging, and production environments.
- Optimize data workloads for performance, scalability, reliability, and cost.
- Develop and maintain CI/CD pipelines for data engineering applications and infrastructure.
- Apply Infrastructure-as-Code practices using Terraform or equivalent technologies.
- Support production deployments, incident resolution, root cause analysis, and continuous improvement.
- Maintain technical documentation, operational runbooks, and troubleshooting guides.
- Take ownership of complex engineering initiatives from design through production.
- Conduct code reviews and promote engineering best practices.
- Mentor junior and mid-level engineers and provide technical guidance.
- Collaborate with architecture, DevOps, product, and other technology teams.
Our data team has expertise across engineering, analysis, architecture, modeling, machine learning, artificial intelligence, and data science. This discipline is responsible for transforming raw data into actionable insights, building robust data infrastructures, and enabling data-driven decision-making and innovation through advanced analytics and predictive modeling.
As a Data Engineer at Endava you will:
- Data Engineering & Architecture
- Design, develop, and maintain scalable ETL/ELT pipelines for data ingestion, transformation, validation, and delivery.
- Develop reusable, modular, and configuration-driven data processing solutions.
- Contribute to technical architecture and evaluate solutions based on scalability, performance, reliability, and maintainability.
- Design and optimize data models, SQL queries, stored procedures, and data processing workflows.
- Workflow Orchestration & Data Quality
- Design and maintain Apache Airflow workflows, including scheduling, dependencies, retries, monitoring, and error handling.
- Develop automated data validation and quality checks using DBT and SQL.
- Implement appropriate monitoring, alerting, and observability for critical data pipelines.
- Troubleshoot and resolve complex data processing and quality issues.
- Cloud & Platform Engineering
- Develop data solutions using AWS and cloud-based data warehouse technologies such as Snowflake.
- Work with cloud services for data storage, processing, compute, messaging, and serverless workloads.
- Support data platforms across development, QA, staging, and production environments.
- Optimize data workloads for performance, scalability, reliability, and cost.
- CI/CD & Production Support
- Develop and maintain CI/CD pipelines for data engineering applications and infrastructure.
- Apply Infrastructure-as-Code practices using Terraform or equivalent technologies.
- Support production deployments, incident resolution, root-cause analysis, and continuous improvement.
- Maintain technical documentation, operational runbooks, and troubleshooting guides.
- Technical Leadership
- Take ownership of complex engineering initiatives from design through production.
- Conduct code reviews and promote engineering best practices.
- Mentor junior and mid-level engineers and provide technical guidance.
- Collaborate with architecture, DevOps, product, and other technology teams.
- Programming: Python, SQL
- Orchestration: Apache Airflow or equivalent
- Data Transformation: DBT, SQL, PySpark
- Data Warehouse: Snowflake or equivalent cloud data warehouse
- Cloud: AWS or equivalent cloud platform
- AWS Services: S3, EMR, Lambda, SNS/SQS or equivalent
- CI/CD: Jenkins, GitHub, GitHub Actions, or equivalent
- 5+ years of professional experience in data engineering or a related software engineering role.
- Strong hands-on experience building and supporting production-grade data pipelines.
- Strong knowledge of Apache Airflow, including DAG development, scheduling, dependencies, retries, and monitoring.
- Strong experience with Snowflake or equivalent cloud data warehouse technologies.
- Proven experience with DBT.
- Solid experience with AWS or another major cloud platform.
- Experience with CI/CD and Infrastructure-as-Code practices.
- Strong programming skills in Python and SQL.
- Demonstrated experience troubleshooting complex production issues and performing root cause analysis.
- Ability to independently own complex technical initiatives from design through implementation and production.
- Strong communication, problem-solving, and technical documentation skills.
- Experience with large-scale data processing.
- Experience with PySpark and EMR.
- Experience mentoring engineers and contributing to technical standards and architecture.
Discover some of the global benefits that empower our people to become the best version of themselves:
- Finance: Competitive salary package, value-based recognition awards, referral bonus;
- Career Development : Career coaching, global career opportunities, non-linear career paths, internal development programmes for management and technical leadership;
- Learning Opportunities: Complex projects, rotations, internal tech communities, training, certifications, coaching, online learning platforms subscriptions, pass-it-on sessions, workshops, conferences;
- Work-Life Balance: Hybrid work and flexible working hours, employee assistance programme;
- Health: Global internal wellbeing programme, access to wellbeing apps;
- Community: Global internal tech communities, hobby clubs and interest groups, inclusion and diversity programmes, events and celebrations.
At Endava, we’re committed to creating an open, inclusive, and respectful environment where everyone feels safe, valued, and empowered to be their best. We welcome applications from people of all backgrounds, experiences, and perspectives—because we know that inclusive teams help us deliver smarter, more innovative solutions for our customers. Hiring decisions are based on merit, skills, qualifications, and potential. If you need adjustments or support during the recruitment process, please let us know.
Coderio designs and delivers scalable digital solutions for global companies. We combine strong technical expertise with a product mindset to lead complex software initiatives end-to-end. We work with international clients, value autonomy and clear communication, and build long-term partnerships through technical excellence.
More information:
We are looking for a Senior Data Engineer to design, build, and optimize scalable, high-performance data platforms supporting large volumes of financial and transactional data. The ideal candidate has strong expertise in Python, SQL, Apache Spark, AWS, and modern data engineering architectures , with proven experience working with production-grade systems in fast-paced environments.
Candidates must reside exclusively in Argentina, Brazil, or Uruguay.
- Design, build, and maintain high-throughput, low-latency batch and streaming data pipelines to ingest and process financial transactions from diverse global sources.
- Design, scale, and optimize cloud data warehouse and lakehouse architectures capable of handling massive volumes of structured and unstructured data.
- Collaborate with Data Scientists, Software Engineers, and Product Managers to understand business needs and translate them into scalable, reliable data solutions.
- Implement and enforce data quality frameworks, automated testing, monitoring, and alerting to ensure data integrity, reliability, high availability, and compliance with SLAs.
- Drive the adoption of DataOps practices , including CI/CD, workflow automation, and Infrastructure as Code (IaC) for data systems.
- Champion data governance, privacy, and security standards across data storage and compute layers, including GDPR/LGPD compliance.
- Mentor and guide junior and mid-level Data Engineers , promoting engineering excellence, best practices, and modern architectural patterns.
- 5+ years of experience in Data Engineering, Big Data, or related Software Engineering roles, with a proven track record managing high-volume, production-grade data systems in fast-paced environments.
- Strong proficiency in Python and SQL for complex data processing, optimization, and software development; Scala or Java experience is a plus.
- Hands-on experience with Apache Spark/PySpark, Delta Lake, and modern lakehouse architectures , including Data Mesh principles.
- Strong expertise in AWS data services , particularly S3, Glue, Athena, EventBridge, Firehose, and Lambda . ......
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