Technical Data Analyst Or Software Engineer Jobs

Strong SQL skills are essential; experience writing complex queries spanning multiple tables is

7+ years of experience in IT and data base/data warehouse domain

Working knowledge of performance tuning of database queries (understanding the inner working of the query optimizer, query plans, indexes, partitions etc.).

Experience in writing sqls in Hive, Impala

Exposure to scripting language like shell scripting, python is required.

Position: Tech Data Analyst (DA)

Commit to professional development and continuous experiential learning to build cross-functional knowledge and technical skill development

One plus years of relevant data analyst experience

Bachelor's degree in statistics, econometrics, mathematics, actuarial science, or a related quantitative field [or equivalent work experience]

Strong oral and written communication skills, demonstrating the ability to convey complex terminology and concepts into appropriate terms for stakeholders.

Python, AWS and machine learning techniques knowledge an asset

Functional knowledge of P&C/Life Insurance lines of business an asset

Version Control Systems Knowledge: Such as Git, for code collaboration and management

Project Management Skills: Ability to manage multiple projects and deadlines

Build flexible solutions that can adapt quickly to changing requirements

4+ years of experience programming in Python and SQL

PySpark Experience: Nice to have

Experience with ETL Tools and Processes: Such as Apache Airflow, Informatica, for extracting, cleansing, and standardizing data

5+ years of hands-on experience in big-data field: HDFS, Spark, SQL, Airflow, Kafka, batch & streaming.

Excellent knowledge of Scala or Java.

Experience with critically important and high performance distributed systems.

Excellent communication skills, teamwork, and proven ability to work in a multi-functional environment.

Proven track record designing, launching and scaling production quality data pipelines.

Deep understanding of computer science fundamentals: complexity and data structures.

Experience in Linux or Unix development environment.

Experience with software development tools (IDE, git) and software development life cycle.

Extensive knowledge of IR Design, Query Optimization, Scheduling, Runtime.

Experience in distributed systems is an asset.

Experience in development or research of data analytics frameworks (such as Spark, Flink) is an asset.

Design, develop framework/engine for the next-generation data analytics.

Bachelor’s degree in data science/machine learning or a quantitative discipline and 5+ years industry experience.

Strong ability in Python (experience with pandas, scikit, NumPy and similar common packages) and SQL

Experience with geographic data a big plus. Geospatial analysis tools (ArcGIS, QGIS),libraries (Geopandas) and formats (Shapefiles)

Self-motivated and able to manage daily priorities with minimal oversight and direction

Benefits and Perks for Full-time Staff

Integrating a growing set of data sources, ingesting, cleaning, and processing them for use in our modeling processes

Expert knowledge of relational database modeling concepts, SQL skills, proficiency in query performance tuning, and desire to share knowledge with others.

3-5 years minimum experience in a production level Data Engineering role building pipelines using Python.

You value the importance of defining data contracts, and have experience writing specifications including REST APIs.

Experience moving trained machine learning models into production data pipelines.

Experience building cloud-native applications and supporting technologies / patterns / practices including: AWS, Docker, CI/CD, DevOps, and microservices.

You have implemented analytics applications using multiple database technologies, such as relational, multidimensional (OLAP), key-value, document, or graph.

Minimum 2 years of related experience.

Coachable, fast learner who can pick up new skills and processes quickly

Analytical mindset with a skillset focused on extracting & analyzing data

Knowledge of programming languages SQL, PowerQuery M, R, or Python

Knowledge of Microsoft Power Platform Power BI/Automate/Apps

Support the Data Team with deep ad-hoc analysis that will drive performance and keep Sales and Customer teams accountable

Experience working with product owners to understand and implement business requirements

2+ years of programming experience, ideally in a compiled language (C#, Java, Go, etc.).

Experience developing and extending systems of moderate complexity

Practical experience writing Map/Reduce, Spark or Hive/Presto or using a machine learning frameworks

Experience working well in a very fast-paced and continuously changing environment

Create high quality, maintainable code that processes and analyzes almost 400 million events daily (and doubling every year)

Manage existing solutions for data management and integration to enable institutional analysis and strategic research functions within Business Intelligence and Analytics

Understanding of data quality management practices

Strong analytical capabilities and critical thinking skills

Develop project plans complete with the collection and translation of business requirements into business intelligence solutions, resource needs and timelines

Maintain currency in the field of data warehousing and BI in the post-secondary sector; share new knowledge with BI&A team members

Experience implementing data integration solutions

Support Microsoft 365 and Azure environments, including Azure AD, Endpoint Management, conditional access, Windows 365, Azure Virtual Desktop

Past experience at a Managed Service Provider required.

At least 3 years of experience implementing and supporting Active Directory networks.

At least 3 years of experience troubleshooting Windows server and desktop operating systems.

Any additional industry certifications such as Citrix, Datto, VMware, Cisco, or HPe are beneficial.

Open and address complex service issues which may arise via phone, email, or office walk-ins.

BA/BS degree in Computer Science, Electrical Engineering, or equivalent practical experience in software engineering.

At least 5 years experience as a software engineer in an industry setting.

Demonstrated experience with Go, Java, Python, and/or SQL.

Experience with designing and implementing scalable data processing pipelines with Bioquery or other analytics-oriented databases.

Education or exposure to healthcare or life sciences, with emphasis on HL7 FHIR.

Work closely with the development team to design, develop, and deliver new software features across the Verily tech stack.