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Senior Data Engineer (with Spark, Airflow)

Company Description

Accesa is a leading technology company headquartered in Cluj-Napoca, with offices in Oradea, Bucharest, Timisoara and 20 years of experience in turning business challenges into opportunities and growth.

A value-driven organisation, it has established itself as a partner of choice for major brands in Retail, Manufacturing, Finance, and Banking. It covers the complete digital evolution journey of its customers, from ideation and requirements setup to software development and managed services solutions.

With more than 1,200 IT professionals, Accesa also has a fast-growing footprint, establishing itself as an employer of choice for IT professionals who are passionate about problem-solving through technology. Coming together in strong tech teams with a customer-centric approach, they enable businesses to grow, delivering value for our clients, partners, industry, and community.

Job Description

One of our clients operates prominently in the financial sector, where we enhance operations across their extensive network of 150,000 workstations and support a workforce of 4,500 employees. As part of our commitment to optimizing data management strategies, we are migrating data warehouse (DWH) models into data products within the Data Integration Hub (DIH). 

Responsibilities:

  • Drive Data Efficiency: Create and maintain optimal data transformation pipelines.  
  • Master Complex Data Handling: Work with large, complex financial data sets to generate outputs that meet functional and non-functional business requirements.  
  • Lead Innovation and Process Optimization: Identify, design, and implement process improvements such as automating manual processes, optimizing data delivery, and re-designing infrastructure for higher scalability. 
  • Architect Scalable Data Infrastructure: Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using open-source technologies. 
  • Unlock Actionable Insights: Build/use analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.  
  • Collaborate with Cross-Functional Teams:Work clients and internal stakeholders, including Senior Management, Departments Heads, Product, Data, and Design teams, to assist with data-related technical issues and support their data infrastructure needs. 

Qualifications

Must have:

  • 5+ years of experience in a similar role, preferably within Agile teams 
  • Skilled in SQL and relational databases for data manipulation 
  • Experience in building and optimizing Big Data pipelines and architectures 
  • Familiarity with innovative technologies in message queuing, stream processing, and scalable big data storage solutions 
  • Knowledge of Apache Spark framework and object-oriented programming in Java; experience with Python is a plus.   
  • Proven experience in performing data analysis and root cause analysis on diverse datasets to identify opportunities for improvement.  
  • Experience with ETL processes, including scheduling and orchestration using tools like Apache Airflow (or similar) 
  • Automate CI/CD pipelines using ArgoCD, Tekton, and Helm to streamline deployment and improve efficiency across the SDLC 
  • Manage Kubernetes deployments (e.g. OpenShift), focusing on scalability, security, and optimized container orchestration 
  • Strong analytical skills in working with both structured and unstructured data 

 

Nice to have:  

  • Expertise in processing large, disconnected datasets to extract actionable insights 
  • Technical skills in the following areas are a plus: relational databases (e.g. PostgreSQL), Big Data Tools: (e.g. Databricks), and workflow management (e.g. Airflow), and backend development using Spring Boot. 

Additional Information

Enjoy our holistic benefits program that covers the four pillars that we believe come together to support our wellbeing, covering social, physical, emotional wellbeing, as well as work-life fusion.

  • Physical: premium medical package for both our colleagues and their children, dental coverage up to a yearly amount, eyeglasses reimbursement every two years, voucher for sport equipment expenses, in-house personal trainer
  • Emotional: individual therapy sessions with a certified psychotherapist, webinars on self-development topics
  • Social: virtual activities, sports challenges, special occasions get-togethers
  • Work-life fusion: yearly increase in days off, flexible working schedule, birthday, holiday and loyalty gifts for major milestones

Average salary estimate

$100000 / YEARLY (est.)
min
max
$80000K
$120000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Senior Data Engineer (with Spark, Airflow), Accesa

As a Senior Data Engineer at Accesa, based in the vibrant tech hub of Romania, you'll be stepping into a role where your expertise in Spark and Airflow can truly shine. Accesa is renowned for transforming challenges into growth opportunities, especially within the financial sector, and you will be a crucial part of this mission. Imagine working with complex financial datasets and creating efficient data transformation pipelines that help optimize data management strategies while collaborating with cross-functional teams. Your role isn't just about handling data; it's about innovating and improving processes, automating manual tasks, and influencing data architecture from the ground up. You'll be leveraging cutting-edge technologies to extract valuable insights that drive business performance metrics, all while enjoying a culture that values social, physical, and emotional well-being through holistic benefits. With 5+ years of experience under your belt, particularly in Agile environments, you're set to tackle the challenges of building scalable infrastructures and optimizing ETL processes using tools you know best, like Apache Spark and Airflow. Here at Accesa, we empower our employees to create meaningful change and have fun while doing it, ensuring that you can blend work with a fulfilling lifestyle. You'll have the opportunity to work remotely, stimulate your curiosity, and enjoy a supportive environment along the way. Join us on this exciting journey to continue pushing boundaries in data engineering!

Frequently Asked Questions (FAQs) for Senior Data Engineer (with Spark, Airflow) Role at Accesa
What are the main responsibilities of a Senior Data Engineer at Accesa?

As a Senior Data Engineer at Accesa, your primary responsibilities include driving data efficiency by creating optimal data transformation pipelines, working with large complex financial datasets, and identifying process improvements for higher scalability. You will collaborate with various stakeholders to support their data infrastructure needs and unlock actionable insights through innovative analytics tools.

Join Rise to see the full answer
What qualifications are necessary for a Senior Data Engineer role at Accesa?

To succeed as a Senior Data Engineer at Accesa, candidates should have 5+ years of experience in a similar role, proficiency in SQL and relational databases, and familiarity with Apache Spark and ETL processes. Additionally, experience working with Big Data architectures and management of Kubernetes deployments is highly advantageous.

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How does Accesa support the growth of its Senior Data Engineers?

Accesa emphasizes personal and professional growth, offering a range of benefits that support employees' well-being. This includes access to training, flexible working schedules, therapy sessions with certified professionals, and opportunities for teamwork through virtual activities and sports challenges.

Join Rise to see the full answer
What technologies do Senior Data Engineers at Accesa typically work with?

In the role of Senior Data Engineer at Accesa, you will typically engage with modern technologies such as Apache Spark, Airflow, and various big data tools, including Databricks. Proficiency in managing Kubernetes deployments and automating CI/CD pipelines will also be utilized to ensure efficient deployment processes.

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What is the work culture like at Accesa for a Senior Data Engineer?

The work culture at Accesa is built on collaboration, innovation, and support. Senior Data Engineers are encouraged to explore new ideas, improve processes, and are provided with a flexible work environment that values work-life balance, leading to a fulfilling career journey.

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Common Interview Questions for Senior Data Engineer (with Spark, Airflow)
Can you explain your experience with Apache Spark in your previous roles?

Be prepared to discuss specific projects where you used Apache Spark to process large datasets. Highlight your understanding of Spark's capabilities, such as distributed computing, and share examples of how you optimized Spark jobs to improve performance.

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How do you approach building and maintaining data pipelines?

Share your systematic approach to designing data pipelines, emphasizing best practices for data ingestion, transformation, and delivery. Discuss the tools you use, challenges you've faced, and how you've leveraged Airflow for orchestration.

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Describe a time you automated a manual process. What were the results?

Provide a detailed account of a specific scenario where you identified a manual task and the steps you took to automate it. Discuss the tools used, the impaction on efficiency, and how it contributed to the overall success of your team or project.

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What’s your experience with CI/CD in relation to data engineering?

Your answer should highlight your experience with CI/CD pipelines in the context of data engineering projects. Discuss specific tools you've used like ArgoCD and Tekton, and how automation improved your deployment process.

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How do you ensure the quality of data in your pipelines?

Talk about the measures you take for data validation and quality checks throughout the data pipeline process. Highlight the importance of monitoring and logging, as well as any tools you use to maintain data integrity.

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Can you share your approach to troubleshooting data issues?

Describe your systematic approach to identifying and resolving data issues. This could include analyzing logs, performing root cause analysis, and how you collaborate with team members to address complex problems.

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What tools do you use for data visualization and analysis?

Discuss your experience with specific tools and platforms for visualizing and analyzing data, outlining your understanding of how to translate raw data into actionable insights for stakeholders.

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What strategies do you use for optimizing large datasets?

Share your strategies for optimizing big data processing, such as proper partitioning, indexing, and employing efficient algorithms. Provide examples from past experiences that demonstrate your successful optimization projects.

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How do you handle the collaboration between data engineering and other teams?

Showcase your communication and collaboration strategies when working with cross-functional teams. Highlight past experiences where you aligned data engineering goals with business needs and how you facilitated discussions.

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What excites you about the data engineering field?

Express your passion for data engineering and why it's an exciting field for you. You can mention emerging technologies, continuous learning opportunities, and the impact of data-driven decisions in business success.

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Accesa was founded in 2004 and is an IT company that was created in response to the growing demand for professional IT services in Western Europe. Its success story in the DACH region is supported and promoted by its offices in Frankfurt, Munich, ...

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Full-time, remote
DATE POSTED
December 12, 2024

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