Talantix.io
Remote Position•12.03.26
AI SCORE 8.5

Senior Data Platform Engineer - Python/​AWS for Finance

$140K–$180K/year
RemoteFinTech
Python•AWS•ETL•Data Pipelines•Docker•Kubernetes•SQL•Data Warehousing•CI/CD

About the Role

We are seeking a Senior Data Platform Engineer to join our dynamic team in the finance sector. This Senior Data Platform Engineer remote position offers the opportunity to work with cutting-edge technologies such as Python and AWS, while contributing to innovative financial solutions. You will play a crucial role in designing and implementing data pipelines that support our data-driven decision-making processes.

What You'll Do

  • Design and develop scalable data pipelines using Python and AWS.
  • Implement data integration solutions to support various data sources and formats.
  • Collaborate with cross-functional teams to ensure data quality and reliability.
  • Utilize Docker and Kubernetes for containerization and orchestration of data services.
  • Lead the development of DataOps practices to streamline data workflows.
  • Monitor and optimize data processes for performance and efficiency.
  • Contribute to the architecture of our data lakehouse and ensure best practices in data warehousing.
  • Participate in incident management and site reliability engineering to maintain high availability of data services.

Requirements

  • 5+ years of experience as a Data Platform Engineer or similar role.
  • Strong proficiency in Python and experience with AWS services.
  • Experience with data warehousing solutions and ETL processes.
  • Familiarity with containerization technologies such as Docker and Kubernetes.
  • Knowledge of SQL and data modeling techniques.
  • Experience with CI/CD practices and tools.
  • Strong problem-solving skills and ability to work independently.
  • Excellent communication skills to collaborate with technical and non-technical stakeholders.

Nice to Have

  • Experience with Ruby on Rails and React.
  • Familiarity with DataOps methodologies.
  • Knowledge of distributed systems and transaction-heavy architectures.

What We Offer

  • 100% Remote Work with flexibility.
  • Highly Competitive USD Pay.
  • Paid Time Off policies for well-being.
  • Autonomy in managing work time.
  • Opportunities to work with Top American Companies.
Why This Job8.5 of 10

This Senior Data Platform Engineer role offers a unique opportunity to work remotely in the finance sector, utilizing advanced technologies like Python and AWS. With competitive pay and flexible work arrangements, it's an attractive position for experienced data professionals.

Salary Range
Required
0/1
Optional
0/1
Bonus
0/1

Who Will Succeed Here

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Proficient in building scalable ETL processes using Python and AWS services like Lambda, Glue, and S3, ensuring efficient data flow and storage.

→

Strong experience with container orchestration tools such as Docker and Kubernetes, enabling seamless deployment and management of microservices in a cloud environment.

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Deep understanding of financial data structures and compliance requirements, coupled with a proactive mindset to innovate and optimize data warehousing solutions.

Learning Resources

→Python for Data Science Handbookguide
→AWS Certified Data Analytics - Specialty 2023course
→Building Data Pipelines with Pythonarticle

Career Path

Senior Data Platform Engineer - Python/AWS for Finance(Now)→Lead Data Engineer(1-2 years)→Data Engineering Manager(3-5 years)

Market Overview

Market Size 2024
$15.5B
Annual Growth
11.2%
AI Adoption
45%
Investment
+35%
Labour Demand
+25%
Avg Salary
$130K

Skills & Requirements

Required
PythonAWSETL
Growing in Demand
Machine LearningData GovernanceApache Spark
Declining
Traditional Data WarehousingJDBC/ODBC Data Connections

Domain Trends

Rise of Real-Time Data Processing
The demand for real-time data processing solutions has increased by 40% as businesses seek to make quicker data-driven decisions.
Increased Focus on Data Security
Over 60% of organizations are prioritizing data security measures in their data pipelines, especially in finance, following recent data breaches.
Shift Towards Serverless Architectures
The adoption of serverless architectures in data engineering roles is projected to grow by 50% as companies look to reduce infrastructure costs and improve scalability.

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