Data Engineer

• LinkedIn must have.
• They must take the test.

10+ years of experience is a must (not less than 10+ years

• )
• required skillset - Python, SQL, AWS Services (Python/Pyspar

• k)
• We are seeking a highly experienced and hands-on Senior Data Engineer to join our Data Engineering teams. You will play a key role in supplementing existing capacity, upgrading our data architecture, and ensuring the highest quality, performance, and cost-efficiency of our data platforms. The work is focused on critical deliverables for personal investment, personal wealth, and comprehensive data analytics, while preparing the platform for a larger strategic move in the futu

• re.
• Key Responsibili
• tiesDesign, build, and maintain high-performance ETL/ELT data pipelines using Python and PySp
• ark.Apply expert-level coding skills to develop and manage data processing jobs leveraging PySpark for distributed computing across large-scale datas
• ets.Take full ownership of the data workflow, including getting data from multiple sources, scrubbing, and validating data to ensure the highest qual
• ity.Write and optimize complex, performant SQL queries for data extraction, integrity checks, and performance tun
• ing.Contribute to platform modernization by exploring and increasing the adoption of AI/ML, including using tools like Copilot and Claude for acceleration, and building models to fill data gaps or improve syst
• ems.Collaborate with data architects by proposing ideas and great questions, taking ownership as the expert on data, pipelines, and syst
• ems.Implement DevOps practices for the automated deployment and orchestration of Python applications and data pipelines (e.g., using Docker, Jenkins, Terrafo
• rm).Hands on experience with SQL and complex performance tun
• ing.Required Technical Sk
• illsProgramming: Expert-level proficiency in Python, including libraries like Pandas and Nu
• mPy.Designing: Designing data pipelines for the data coming from multiple sou
• rcesData Processing: Solid hands-on experience with PySpark for building scalable data workf
• lowsData Querying: Expert-level knowledge of writing complex SQL queries (Oracle or Snowflake), with proven ability to perform performance tuning on large datasets and complex database c
• ode.Cloud Platform: Strong experience with AWS cloud services and associated data services, specifica
• lly:AWS Glue (
• ET
• L)S3La
• mbdaReds
• hiftDynamoDB, Athena, ECS, EventBridge, OpenSearch,
• RDSETL & Data Management: Strong proficiency in ETL/ELT methodologies and tools, as well as Data Quality, Data Validation, and Anomaly Detection techniq
• ues.Scripting: Working experience with scripting and automation using Unix and Pyt
• hon.Desired Skills & Professional Attrib
• utesFamiliarity with AI/ML and Large Language Model (LLM) approaches to data analysis and validat
• ion.Knowledge of data warehousing concepts and data modeling techniq
• ues.Experience with DevOps, Continuous Integration, and Continuous Delivery (e.g., Jenkins, GitH
• ub).Experience with BI Reporting tools such as Power BI or Tabl
• eau.Strong preference for candidates with prior experience in the investment data dom
• ain.Ability to work independently through complex data challenges and strong analytical and problem-solving ski

lls.