Data Engineer / Data Scientist (Azure) || Hybrid

In this role, we are seeking a data engineer to design, implement, and optimize cloud-based data

pipelines using Microsoft Azure services including ADF, Synapse, and ADLS.

Responsibilities

• Collaborate with our business analytics and data science teams, gathering requirements and

delivering complete business intelligence solutions

• Mentor junior software developers and build a strong team
• Model data and metadata to support discovery, ad-hoc, and pre-built reporting
• Design and implement data pipelines using Hadoop, Spark, and Azure services such as Blob

Storage, SQL Database, Event Hubs, Data Factory, Synapse Analytics, and Databricks

• Should be able to write Programs & Scripting, Strong in SQL, Proficiency in Python or Scala.

Experience with PowerShell or Azure CLI for automation is a plus

• Partner with security, privacy, and legal teams to deliver solutions that comply with security and

privacy policies

• Own the design, development, and maintenance of datasets our business analytics teams will

use to drive key business decisions

• Develop and promote standard methodologies in data engineering, including scalability,

reusability, maintainability, and usability

• Tune and ensure compute performance by optimizing queries, databases, files, tables, and

processes

• Ensure data and report service level agreements are met
• Analyze and solve problems at their root, stepping back to understand the broader context
• Own continuous engineering operational excellence of the datasets that drive key business

decisions

• Learn and understand a broad range of data resources and know when, how, and which to use

and which not to use

• Keep up to date with advances in big data technologies and run pilots to design the data

architecture to scale with increased data volume using Azure

• Continually improve ongoing reporting and analysis processes, automating or simplifying

self-service support for datasets

• Triage many possible courses of action in a high-ambiguity environment, making use of both

quantitative analysis and business judgment

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Qualifications we seek in you!

Minimum Qualifications / Skills

• Bachelors degree in computer science or related technical field
• 10+ years of experience in data architecture and business intelligence
• 5+ years of experience in developing solutions in distributed technologies such as Hadoop, Spark
• Experience in delivering end-to-end solutions using Azure services Blob Storage, SQL Database,

Event Hubs, Data Factory, Synapse Analytics, and HDInsight

• Experience in programming using Python, Java, or Scala
• Expert in data modeling, metadata management, and data quality
• SQL performance tuning
• Strong interpersonal and multitasking skills with the ability to balance competing priorities
• Excellent communication (verbal and written) and interpersonal skills and an ability to effectively

communicate with both business and technical teams

• An ability to work in a fast-paced, ambiguous environment where continuous innovation is

occurring

• Experience with a business intelligence reporting tool

Preferred Qualifications/ Skills

• Experience with Databricks for advanced analytics and data processing
• Understanding of well-architected data pipeline designs
• Expertise in monitoring and fault-tolerant pipeline designs
• Knowledge of cluster configuration for optimal performance
• Ability to create cost-optimal solutions
• Experience in exploratory data analysis (dashboarding, plotting) using machine learning

technologies and algorithms is desirable

• Good knowledge of standard machine learning techniques (like regression, classification,

anomaly detection, forecasting) by using standard machine learning libraries part of Spark,

Python is desirable

• Prior experience in gen AI and related tools and techniques (such as large language models,

prompt engineering) is desirable

• Having a relevant Azure certification (architecture/data/machine learning) is desirable