Senior Data Engineer in Finance Tribe

FinanceTech Python

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Join us in our quest to provide fast and accurate financial information to investors, regulators, and internal decision-makers, while optimising the management of financial resources. Your advanced expertise in Python programming and data engineering will be instrumental in leading the development of a scheduling platform on AWS, and in creating data transformations, monitoring, and reconciliation processes in Python.

Your role as a Senior Data Engineer will place you as a prominent leader in our dynamic team focused on the Daily Profit & Loss application. You will drive the development of a new AWS-based platform and ensure a seamless migration of ELT, data monitoring, and reporting scripts from SAS to Python. You will collaborate with and mentor a self-driven, cross-functional agile squad, including Analysts, Engineers, and DevOps professionals. We assure you ample opportunities for growth using a modern technology stack and AWS Cloud services.

The Finance Tribe ensures Danske Bank’s financial potential, benefiting customers, colleagues, society, and investors through robust financial management. We ensure this by efficiently overseeing Danske Bank’s finances.

*Depending on your experience and knowledge, we may offer you a different seniority for the role.

You will:

Lead the team in building the target architecture on AWS
Oversee the smooth migration of SAS-based data monitoring and reconciliation solutions to Python
Collaborate closely with the team to build the target architecture on AWS
Ensure smooth migration of SAS based data monitoring and reconciliation solution to AWS native one
Cultivate an agile and collaborative working environment within an internationally distributed squad (Denmark and Lithuania)
Act as a subject matter expert in the Tribe for Data Engineering related questions consulting other squads and engineers on most complex solutions
Define best data engineering practices in the Tribe through collaboration with Chapter Leads and Data Engineering Guild

About you:

You are an experienced data engineer with experience in writing pyspark, python and SQL code
(Optionally) you have experience with SAS programming language
You are proficient at creating, modifying, and maintaining date pipelines using native AWS services in data lake environment as well as creating ETL workflows targeting classic relational databases
Proficiency in Amazon Web Services (AWS), including managing cloud infrastructure with Terraform
You have been a leader with engineering background for some years or at least have a strong inner drive to lead a team of engineers and grow your leadership skills
Strong understanding of the development lifecycle process and a willingness to learn new programming languages, tools, and processes. High level of personal responsibility and commitment to team goals
Advanced English skills

We offer:

Monthly salary range from 4480 EUR to 6720 EUR gross (based on your competencies relevant for the job).

Additionally, each Danske Bank employee receives employee benefits package which includes:

Growth opportunities: professional & supportive team, e-learnings, numerous development programs; (incl. professional certificates); 100+ professions for internal mobility opportunities.
Health & Well-being: a diverse, inclusive, work & life balance work environment; additional health insurance; mental well-being practices; partial psychologist counselling compensation; silence and sleep zones at the office; game rooms.
Hybrid working conditions: Work from home up to two days a week; home office budget (after the probation period); modern Danske Campus workplace developed with anthropologist for the best employee experience.
Additional days of leave: for rest, health, volunteering, exams in higher education institutions, and other important activities. Moreover, for seniority with Danske Bank.
Monetary compensation package: accidents & critical diseases insurance; financial support in case of unfortunate events, travel insurance; IIIrd Pillar Pension Fund contribution.