Position Details

Type Full-Time

Experience mid

Exp. Years 5+ years

Education Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field

Category Data & Analytics

About this role

This role involves architecting, building, and maintaining data pipelines and infrastructure to support advanced analytics and reporting in a financial technology environment.

Key Responsibilities

Architect data pipelines
Build and maintain ETL workflows
Manage data lake infrastructure
Ensure data security and compliance
Collaborate with cross-functional teams

Technical Overview

The technical environment includes Python, SQL, Spark, Hadoop, Airflow, and cloud-based data platforms, focusing on data engineering, data warehousing, and data governance.

Ideal Candidate

The ideal candidate is a mid-level data engineer with 5+ years of experience in building and maintaining ETL pipelines, data lakes, and working with big data frameworks like Spark and Hadoop. They possess strong collaboration skills and experience with cloud-based data architectures.

Must-Have Skills

PythonSQLETL developmentData warehousingData lake managementCloud-based data stack

Nice-to-Have Skills

HadoopSparkHadoopData GovernanceData SecurityData Compliance

Tools & Platforms

Apache SparkHadoopAirflowDBTCloud platforms

Required Skills

PythonSQLETLData LakeSparkHadoopAirflowData GovernanceCloud Data Stack

Hard Skills

PythonSQLETLData LakeSparkHadoopAirflowDBTData GovernanceCloud Data Stack

Soft Skills

collaborationcommunicationproblem-solvingindependent workjudgment

Industry & Role

Industry Finance, Fintech

Job Function Data engineering and infrastructure management

Keywords for Your Resume

Data EngineerETL pipelinesData LakePythonSQLSparkHadoopAirflowData GovernanceData SecurityData ComplianceData WarehousingCloud Data StackData ScienceBig Data

Deal Breakers

Lack of experience with ETL development, No experience with cloud data platforms, Less than 5 years of relevant experience

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