Anblicks
Website:
anblicks.com
Job details:
About The Role
Seeking a skilled
Data Engineer to design, build, and optimize modern data pipelines and analytics platforms. The ideal candidate will have strong hands-on experience with
Snowflake,
dbt,
Airflow, and
Python/Spark, along with solid SQL and data modeling skills. You’ll collaborate with cross-functional teams—data analysts, data scientists, and business stakeholders—to ensure data reliability, scalability, and Performance.
Key Responsibilities
Design, develop, and maintain
data pipelines for ingestion, transformation, and delivery using
Airflow,
dbt, and
Snowflake.
Implement and optimize
ETL/ELT workflows for structured and semi-structured data.
Develop and maintain
data models, schemas, and views in Snowflake to support analytics and reporting.
Build and manage
data processing frameworks using
Spark (PySpark or Spark SQL).
Integrate data from various sources (databases, APIs, files, cloud storage, streaming data).
Monitor data pipelines for performance, reliability, and cost optimization.
Implement
data quality checks, observability, and error handling mechanisms.
Collaborate with data analysts/scientists to understand data needs and deliver scalable solutions.
Apply
CI/CD best practices for data pipeline deployment and version control (Git).
Ensure compliance with
data governance, security, and privacy policies.
Required Skills & Experience
5–7 years of experience in data engineering or a related field.
Strong expertise with
Snowflake (warehousing concepts, performance tuning, cost optimization, security).
Proven experience with
dbt (data modeling, testing, documentation, modular SQL).
Hands-on experience with
Apache Airflow (DAG design, scheduling, orchestration).
Proficiency in
SQL and
Python for data manipulation and automation.
Experience With Apache Spark (PySpark Preferred).
Strong understanding of
ETL/ELT design patterns,
data modeling (Kimball, Data Vault), and
dimensional modeling.
Experience with
Git,
CI/CD, and
Cloud Platforms (AWS, Azure, or GCP).
Knowledge of
data quality, observability, and
monitoring tools (e.g., Great Expectations, Monte Carlo, or similar).
Preferred Skills (Nice To Have)
Experience with
streaming technologies (Kafka, Kinesis, or Pub/Sub).
Exposure to
data cataloging and governance tools (e.g., Collibra, Alation, Amundsen).
Familiarity with
Looker, Power BI, or Tableau for data consumption.
Experience with
infrastructure as code (Terraform, CloudFormation).
Click on Apply to know more.