Senior Data Engineer

About the Company

Tredence focuses on last-mile delivery of powerful insights into profitable actions by uniting its strengths in business analytics, data science and software engineering. The largest companies across industries are engaging with us and deploying their prediction and optimization solutions at scale. Head quartered in the San Francisco Bay Area, we serve clients in the US, Canada, Europe, and South East Asia.

We are seeking an experienced data scientist who apart from the required mathematical and statistical expertise also possesses the natural curiosity and creative mind to ask questions, connect the dots, and uncover opportunities that lie hidden with the ultimate goal of realizing the data’s full potential.

Tredence is an equal opportunity employer. We celebrate and support diversity and are committed to creating an inclusive environment for all employees.

Visit our website for more details :

https : / / www.tredence.com /

Responsibilities

Developing Modern Data Warehouse solutions using Snowflake and ADF.

Ability to provide solutions that are forward-thinking in data engineering and analytics space.

Collaborate with DW / BI leads to understand new ETL pipeline development requirements.

Triage issues to find gaps in existing pipelines and fix the issues.

Work with business to understand the need in the reporting layer and develop a data model to fulfill reporting needs.

Help joiner team members to resolve issues and technical challenges.

Drive technical discussions with client architect and team members.

Orchestrate the data pipelines in the scheduler via Airflow.

Qualifications

Bachelor's and / or master’s degree in computer science or equivalent experience.

Must have total 6+ yrs. of IT experience and 3+ years' experience in Data warehouse / ETL projects.

Required Skills

Expertise in Snowflake security, Snowflake SQL and designing / implementing other Snowflake objects.

Hands-on experience with Snowflake utilities, SnowSQL, Snowpipe, Snowsight and Snowflake connectors.

Deep understanding of Star and Snowflake dimensional modeling.

Strong knowledge of Data Management principles.

Good understanding of Databricks Data & AI platform and Databricks Delta Lake Architecture.

Should have hands-on experience in SQL and Spark (PySpark).

Experience in building ETL / data warehouse transformation processes.

Experience with Open Source non-relational / NoSQL data repositories (incl. MongoDB, Cassandra, Neo4J).

Experience working with structured and unstructured data including imaging & geospatial data.

Experience working in a Dev / Ops environment with tools such as Terraform, CircleCI, GIT.

Proficiency in RDBMS, complex SQL, PL / SQL, Unix Shell Scripting, performance tuning, troubleshooting and Query Optimization.

Databricks Certified Data Engineer Associate / Professional Certification (Desirable).

Comfortable working in a dynamic, fast-paced, innovative environment with several ongoing concurrent projects.

Should have experience working in Agile methodology.

Strong verbal and written communication skills.

Strong analytical and problem-solving skills with a high attention to detail.

Preferred Skills

Snowflake / Azure Data Factory / PySpark.