Senior Data Engineer

Data Engineer

Location : Hybrid onsite, 3 days in Boston (core days : Tues- Thurs)

Duration : 6 months to start, possible extension if all goes well

GC & USC

Skype+ Final round F2F

Financial Service or Asset Management a MUST

Manager Notes : This is a mid- level role that requires expertise in working in data integration. The ideal

candidate has 5+ years of experience and is local to Boston with strong SQL skills. Financial services or asset

management experience is required. This role will be the "go-to" for any tech questions, reviewing code, etc. In

order for the candidate to succeed in this role, they need to work well independently as well as on a team, be

inquisitive, and have excellent communication skills. The bullets highlighted below are crucial for the role.

Experience with Snowflake is a huge plus. The intent is for this role to be long term and will extend if all goes

well.

We are searching for a Lead Data Engineer to implement data engineering and analytics solutions. Primary

responsibilities include full implementation and maintenance of data ingestion, data maintenance, data

validation and data delivery of investment data. We are looking for someone who thrives in an agile,

collaborative, team-based environment, working closely with technology peers across the organization,

investment professionals and key vendor partners.

JOB REQUIREMENTS :

Bachelor's degree in Computer Science or related disciplines.

Minimum of 5 years of experience in design, development and building data oriented complex

applications.

Minimum of 2-4 years of hands-on progressive experience from SQL to Advanced SQL.

Experience working in data integration (ETL / ELT), data warehouse, data analytics architecture and

sound understanding of design principles. Knowledge of and experience with Snowflake and other

cloud native databases is highly preferred.

Development Experience in Cloud based PAAS platforms like Microsoft Azure, Google GCP or Amazon

AWS

Deep understanding of Agile SDLC, DevOps and Cloud technologies required, in addition to exposure

to multiple, diverse technologies, platforms, and processing environments.

Knowledge about various architectures, patterns such as unified data management architecture (UDM),

data mesh architecture, event-driven architecture, real-time data flows, non-relational repositories, data

virtualization, etc.

Experience with building solutions in the financial services domain with an understanding of financial

instruments, transactions, and positions, is desired.

Good interpersonal and communication skills with the ability to lead cross-team collaboration and

partnerships across a variety of internal and external constituencies.