3–5 years of experience in data engineering or analysis., Proficiency in Python and SQL for data manipulation., Experience in data cleaning, root cause analysis, and geospatial analysis., Knowledge of API development and consumption, with familiarity in Agile methodologies..
Key responsibilities:
Perform data cleaning and address mismatch analysis.
Collaborate with stakeholders to improve address validation processes.
Prototype and test API-based address validation solutions.
Present findings and progress within an Agile environment.
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Lean Tech is a rapidly expanding organization situated in Medellín, Colombia. We pride ourselves on possessing one of the most influential networks within software development and IT services for the entertainment, financial, and logistics sectors. Our corporate projections offer a multitude of opportunities for professionals to elevate their careers and experience substantial growth. Joining our team means engaging with expansive engineering teams across Latin America and the United States, contributing to cuttingedge developments in multiple industries.
Currently, we are seeking a Mid+ Data Engineer to join our team. Here are the challenges that our next warrior will face and the requirements we look for:
Position Title: Mid+ Data Engineer
Location: Remote LATAM
What you will be doing:
Lean Tech is seeking a Mid+ Data Engineer to work on an exploratory project with a focus on resolving systemic address mismatches for a prominent U.S. telecom company. The primary purpose of this role is to engage in handson data cleaning, prototyping, and collaborating with stakeholders to enhance address validation accuracy. This position is uniquely challenging as it emphasizes experimentation and iteration over production deployment, allowing for a dynamic exploration of solutions in an Agile environment. As a key member of the data engineering team, you will evaluate and implement innovative techniques, leveraging strong skills in Python, SQL, and geospatial analysis. Your contributions will directly support the companys commitment to professional growth and diversity.
Conduct deep data cleaning and root cause analysis on mismatched customer addresses across systems.
Use SQL and Python to explore, transform, and validate datasets for address accuracy.
Perform geospatial analysis to validate and align address data utilizing metrics such as latitude and longitude.
Prototype and test APIbased solutions, including thirdparty validation tools.
Apply natural language processing techniques to parse and normalize address data.
Collaborate with stakeholders to investigate data anomalies and iterate on solution development.
Present findings, methodologies, and iterative improvements within an Agile environment.
Provide assessments and reports on data health and project progress.
Required Skills & Experience:
3–5 years of experience in data engineering, data analysis, or related roles with a proven track record in designing and implementing data warehousing solutions, preferably in an Enterprise environment.
Advanced proficiency in Python and SQL for data exploration, transformation, and validation.
Strong experience in data cleaning and conducting root cause analysis.
Intermediate experience with geospatial analysis tools or methods.
Proficiency in using APIs, including developing, consuming, or evaluating thirdparty APIs, with the ability to read API documentation, make web requests, and parse responses.
Capability to work with flat files and data extracts from multiple sources.
Intermediate experience with Agile methodologies, particularly Scrum practices.
Excellent problemsolving, communication, and time management skills.
Basic familiarity with natural language processing (NLP) techniques for parsing address data is a plus.
Exposure to data profiling or data health assessment tools is beneficial.
Good to Have:
Experience with geospatial tools such as Lightbox data or GE Smallworld
Knowledge of advanced geocoding techniques and fuzzy logic for data validation
Familiarity with scripting languages other than Python, such as R or JavaScript, for data manipulation
Understanding of cloudbased data solutions and platforms, such as AWS or Google Cloud
Prior experience in telecom data systems or a related field
Certification in data science or a related discipline
Strong adaptability and willingness to learn emerging data technologies
Effective leadership skills and experience in mentoring junior team members
Geospatial analysis packagestools like:
Nominatim
Geopy
Placekey
H3 Indexes
Soft Skills:
Excellent problemsolving and analytical skills.
Strong communication and collaboration abilities, with the capacity to work effectively across different time zones.
Time management skills to prioritize tasks and manage multiple projects simultaneously, ensuring timely delivery and highquality outcomes.
Why you will love Lean Tech:
Join a powerful tech workforce and help us change the world through technology
Professional development opportunities with international customers
Collaborative work environment
Career path and mentorship programs that will lead to new levels.
Join Lean Tech and contribute to shaping the data landscape within a dynamic and growing organization. Your skills will be honed, and your contributions will play a vital role in our continued success. Lean Tech is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Required profile
Experience
Level of experience:Mid-level (2-5 years)
Industry :
Information Technology & Services
Spoken language(s):
English
Check out the description to know which languages are mandatory.